Find Beginner-Friendly Projects: Start with projects offering good first issues, clear documentation and welcoming communities to make your contribution journey easier.Explore Good First Issues: Look for beginner-labelled issues that match your skills, interests and available time before choosing your first contribution.Read Project Documentation: Understand contribution guidelines, coding standards, setup instructions and project expectations before making changes to avoid unnecessary mistakes.Improve Documentation: Documentation fixes are valuable contributions and provide beginners with an accessible way to understand projects while learning collaboration practices.Fix Small Bugs: Start with manageable bugs that help you understand the codebase, project workflow and review process without becoming overwhelming.Add Tests: Writing tests can improve project reliability while helping contributors understand existing functionality, expected behaviour and potential edge cases.Suggest Features Carefully: Discuss proposed features through issues before coding, allowing maintainers and contributors to align on requirements and implementation approaches.Contribute Beyond Code: Design, community support, translations and documentation can also create meaningful value without requiring advanced programming skills.Build Long-Term Relationships: Consistent contributions, respectful communication and responsiveness to feedback can help you become a trusted open-source community member.Read More StoriesJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Overview:Twitch enabled a "Training for Generative AI" setting on August 12, 2026 that opts every streamer in by default.Eligible content includes livestreams, VODs, clips, chat messages, and channel images, and it feeds models used across Amazon, not just Twitch.Streamers must manually disable the toggle in their dashboard, and even then, chat in someone else's channel stays governed by that channel owner's setting.Twitch has made millions of streamers' content available for a new Amazon AI training use by default. The platform switched on a setting that allows livestreams, archived videos, clips, chat logs, and channel images to be used for training Amazon's generative AI models, and it did so without asking anyone first.Twitch framed the announcement as a gift: a new setting that lets creators opt out. The messaging obscured the more uncomfortable fact underneath it, which is that the opt-out only exists because opt-in would have failed. Chief Product Officer Mike Minton said as much during an August 12 livestream watched by nearly three thousand people. Asked why the company did not simply let streamers choose to join, Minton answered plainly: "If this was opt-in, nobody would opt in. That's honestly the answer."That admission turned a routine settings update into a case study on consent design.What Content Is Being Used?Twitch says the training program covers channel content broadly. That includes live broadcasts, videos on demand, clips, highlights, chat messages, on-screen text, and images tied to a channel. Minton offered one concrete example: stream audio could refine Amazon's speech-to-text models, which would then improve automatic captions on Twitch and elsewhere in the Amazon ecosystem. Twitch has said the resulting models may also be applied more broadly across Amazon's product lineup, meaning content trained on for a Twitch feature is not necessarily confined to Twitch.Chat carries its own wrinkle. Whether a message counts as training data depends on the channel owner's setting, not the chatter's own preference. A streamer who opts out still has no control over what happens to a comment they post in someone else's chat if that channel leaves the setting enabled.Why Was This Not Really New?Twitch's framing suggested this was the start of something. Reporting suggests otherwise. Ars Technica reported that Minton confirmed this at a 2024 event hosted by The Information. Amazon was already using Twitch data to train AI models. This was happening well before any public setting existed to control it.So what changed on August 12 was not the practice itself. Streamers finally got a labeled switch to try to stop it. That switch applies only to future use. Twitch's own language draws that line carefully. Opting out prevents content from being used for "future" model improvements. The status of anything already used for training remains unaddressed.What Default Setting Could Mean Legally?The default-on approach raises a real question about what meaningful consent looks like. A platform is introducing a new AI use for content people have already posted. Those people posted that content under different assumptions.US privacy regulators have grown more attentive to this issue. They are watching interfaces and disclosures that can leave users unclear about how their data is collected or used. The FTC has said something relevant here. Settings engineered to maximize data capture without a clear affirmative choice can raise concerns under its unfair-or-deceptive-practices authority.None of that means Twitch has broken the law. Whether the arrangement creates legal exposure would depend on the specific terms, the disclosures Twitch gave, the jurisdiction, and how the training program actually operates in practice, none of which is settled by a single quote from a product executive.The more immediate issue is transparency, not liability. Twitch is asking creators to actively reject a new use of their content instead of actively authorizing it, while its own chief product officer said an opt-in version of the same setting would likely see little participation. That gap between what the company built and what it says it expected users to want is what keeps this in the middle of the broader debate over AI-training consent.How To Opt Out?Streamers who want out need to act manually. Head into the Twitch Streamer Dashboard, open Settings, select Security and Privacy, and locate the "Training for Generative AI" toggle near the bottom of the page. Switching it off applies going forward. Some users have already reported the setting reverting to enabled after being turned off, so a periodic check is worth the two minutes it takes.What Streamers Should Actually Do?Treat the opt-out as necessary but not sufficient. Turn it off on the personal channel first. Then check moderator settings on any channel where chat participation happens regularly, since that exposure sits outside personal control. Screenshot the toggle state as a timestamped record, given the reports of it silently re-enabling. Finally, watch for regulatory movement in home jurisdictions, since default-on AI training settings are drawing sustained attention from privacy regulators generally, independent of how this specific case is eventually resolved.Final ThoughtTwitch built a system, then handed streamers the burden of escaping it. The next fight will not be about the toggle. It will be about what already got trained before anyone had one to flip.Also Read: Twitch & GTA Online Unite: Grab GTA$500K, Street Samurai Livery and Exclusive RewardsAlso Read: Australia Bans Twitch, Expands Social Media Age Limits for U-16 UsersYou May Also Like:Best Alternatives to Twitch Studio for Windows for 2025YouTube Monetization Gets Tougher: New Eligibility Rules for Creators ExplainedYouTube YPP Rules: Monetization Bar Doubles in 2027FAQs1. What is Twitch's new AI training setting?Twitch's Training for Generative AI setting allows streamers to control whether eligible channel content can be used for Amazon's generative AI training. The setting is enabled by default.2. How can Twitch streamers opt out of AI training?Go to Twitch → Settings → Security and Privacy → Training for Generative AI and turn the setting off. The change applies to future training.3. What Twitch content can be used for Amazon AI training?The setting covers eligible channel content, including livestreams, videos, clips, highlights, images and chat messages associated with the channel.4. Does opting out remove content that Amazon may have already used for AI training?No. The opt-out is forward-looking and does not automatically remove content that may have already been used or ingested for training before the setting was disabled.5. Does a streamer's opt-out protect their messages in other Twitch chats?No. Chat content is governed by the settings of the channel where the message was posted. A streamer who opts out on their own channel may still have messages used for training if they participate in another channel that has training enabled.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Google has introduced Gboard Rambler, a Gemini-powered voice input feature on the Pixel 11 series, designed to make voice typing cleaner and more useful. Unlike conventional live dictation, Rambler waits until users finish speaking before converting the complete utterance into text.The Pixel 11 series launches in India on August 20, 2026, with prices starting at Rs. 89,999. Rambler is integrated into Gboard and works across apps with text fields, including Messages, Gmail, and Google Docs.How Gboard Rambler WorksRambler can be opened through the microphone icon in the top-right corner of Gboard, marked with Gemini’s spark. A waveform takes over the suggestion strip while the user speaks. Once the checkmark is tapped, the session closes, and the cleaned text appears in the selected field.The approach allows Gemini to receive the complete utterance before processing it. This means Rambler can understand changes made halfway through a sentence. For instance, if a user dictates a shopping list containing apples, bananas, and oranges, and then says they have dropped the apples, the finished list shows two items. Google demonstrated this behavior when it introduced Rambler in May 2026.Rambler also removes filler words such as ‘um’ and ‘ah’, handles repetitions and self-corrections, and can respond to commands to change a message’s style, expand it, or add emoji. Tapping the microphone again allows users to add to or revise the existing text.Standard Voice Typing Still AvailableGoogle has retained the older speech engine under the name Standard. Users can switch between Rambler and Standard in Gboard settings. Google describes Rambler as a way to ‘focus on your thoughts, and revise in your own words’, while Standard remains available for users who want word-for-word dictation. This distinction could matter for addresses, code, or exact names, where rewriting based on intent may not be suitable.A separate Personal Dictionary setting can also help Rambler handle relevant terms, including names, brands and Indian place names.Also Read: iPhone vs Pixel: Google Pixel Wins the AI Photo Editing TestGemini Expands Across GboardRambler is part of a wider Gemini push inside Gboard. Sign-to-text is also included in the same Gboard release, using DeepMind’s Sign Language-to-Text model to convert American Sign Language into written text inside the keyboard and Live Transcribe.Google says the training set contains more than 100,000 hours of sign-language data across more than 50 languages. Gemini also powers an upgraded autofill feature in the suggestion strip, although it requires explicit opt-in.Pixel 11 Price and AvailabilityPre-orders opened on August 12, 2026, while retail sales begin on August 20 through the Google Store, Flipkart, and authorized partners. The Pixel 11 starts at Rs. 89,999 for 12GB of RAM and 256GB of storage, while the Pixel 11 Pro, Pixel 11 Pro XL, and Pixel 11 Pro Fold start at Rs. 1,19,999, Rs. 1,34,999, and Rs. 1,86,999, respectively.Rambler debuts on the Pixel 11, Pixel 11 Pro, Pixel 11 Pro XL, and Pixel 11 Pro Fold. Google says wider Android availability will follow later, while the feature remains limited to select countries and languages at launch.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Hackers are using BNB Smart Chain to store malicious instructions while fake CAPTCHA pages trick Windows users into executing malware. Microsoft Threat Intelligence linked the campaign to EtherHiding, which places attacker commands inside blockchain smart contracts.Attackers first compromise legitimate websites and inject JavaScript into them. That code connects to BNB Chain infrastructure and retrieves instructions from a smart contract tied to the ClearFake malware campaign.  The blockchain does not infect devices by itself. Instead, attackers rely on social engineering to persuade visitors to execute the retrieved commands on their computers.Fake CAPTCHA Pages Turn Visitors Into Malware RunnersVictims see what appears to be a normal CAPTCHA verification page after visiting a compromised website. The page then asks them to open Windows Run, paste clipboard content and press Enter. That action launches attacker-controlled instructions. Microsoft calls this technique ClickFix, while another version called TerminalFix directs victims to Windows Terminal or PowerShell.Why would a routine CAPTCHA ever need access to Windows Run or PowerShell? Microsoft says legitimate CAPTCHA checks should never require users to paste commands into system tools. Attackers can also misuse built-in Windows utilities, including PowerShell, cmd, rundll32 and scheduled tasks. Successful infections can expose passwords, steal credentials and create persistent access.BNB Chain Storage Makes Malicious Commands Harder to RemoveEtherHiding changes where attackers keep part of their malware infrastructure. Instead of depending only on conventional servers, they place malicious instructions inside blockchain smart contracts.Security teams can often block or remove malicious websites and command servers. Blockchain data creates a tougher challenge because changing the relevant contract requires control of its associated wallet.This resilience gives attackers a storage layer that remains widely accessible. Still, they need compromised websites and deceptive prompts to turn stored instructions into an infection. Microsoft said ClickFix and TerminalFix campaigns target thousands of consumer and enterprise devices globally each day. The resulting access can support deeper corporate network compromises.Also Read: FBI Arrest in Steam Malware Scam, Hackers Steal $220,000 in CryptocurrencyCampaign Builds on Earlier Blockchain Malware TechniquesAttackers have used blockchain infrastructure in earlier malicious operations. Previous campaigns have relied on Bitcoin transactions and networks, including TRON, Aptos, and BNB Chain.The technique does not expose a flaw unique to the BNB Chain. Instead, attackers exploit public blockchain infrastructure because it offers persistence, accessibility, and resistance to centralized removal.Once malware gains access, attackers can steal credentials, maintain persistence, and move deeper into corporate environments. Microsoft said such access could eventually support ransomware attacks or wider network compromises. For users, the warning remains direct. Legitimate CAPTCHA systems do not ask visitors to paste commands into Windows Run, Command Prompt, Terminal, or PowerShell.ConclusionMicrosoft’s findings show attackers are combining persistent blockchain storage with fake CAPTCHA prompts to deliver Windows malware. The BNB Chain itself does not infect users, but malicious smart-contract data can resist removal. Users should reject any CAPTCHA that asks them to open system tools or paste commands.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

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OverviewFunction calling lets an OpenAI model request an action by name, but the model never runs code itself; the application executes it and returns the result.The mechanism follows a five-step loop: a question arrives, the model picks a function, the backend runs it, the result returns, and the model writes a final answer.Structured Outputs and function calling solve different problems, and mixing them up leads to the wrong tool for the job.Ask an OpenAI model to run a live calculation that depends on current data, and relying on the model's own output is not the same as running a real calculator or function. Ask it to check today's weather in a specific city, and it has no way to reach outside its training data. Function calling exists to close that gap, turning a model that can only talk into one that can act.What Function Calling Actually DoesFunction calling connects an OpenAI model to external tools and systems. A developer describes a set of functions using a JSON schema: names, descriptions, and the arguments each one accepts. When a user sends a message, the model checks whether an available function matches it. If one does, the model does not execute anything on its own. It returns a structured JSON object naming the function and its arguments.That separation is deliberate. The model never touches a database, an API key, or business logic directly. The application receives the JSON, validates it, runs the actual function, and decides what happens next. Authentication and sensitive operations stay on servers the model cannot reach.The Five-Step Loop Behind Every Tool CallEvery function call follows the same pattern, regardless of what the function does.A user sends a question or request.The model reviews the available tools and selects one, along with arguments, or decides no tool is needed at all.The application executes that function using real code.The result gets sent back to the model as part of the conversation.The model reads that result and writes a natural-language reply.Developers can steer step two directly: auto lets the model decide, required forces a call, and none turns off tool use for that turn. This loop is what makes agents possible. A single message can trigger several rounds of this cycle before a final answer appears, and some requests call several functions at once, in parallel, rather than one at a time.Function Calling vs Structured OutputsThe two features get confused often, though they solve different problems. Function calling means "do something." Structured Outputs means "return something in this format."A workflow can use both together: a function call retrieves data, and Structured Outputs formats the final response.A Practical Example: Building a Weather AssistantConsider a simple assistant meant to answer weather questions. The developer defines a function called get_current_temperature, with a required argument for location. That definition gets included in the request alongside the user's message, something like this:{  "name": "get_current_temperature",  "description": "Get the current temperature for a given location,"  "parameters": {    "type": "object",    "properties": {      "location": { "type": "string" }    },    "required": ["location"]  }}A user asks about the weather in Lisbon. The model does not answer directly. It returns a tool called get_current_temperature with the argument "location": "Lisbon." The application reads that request, calls a real weather API, and gets back a value such as 21 degrees Celsius. That result gets appended to the conversation as a tool response, tied to the original call by its ID:{  "role": "tool",  "tool_call_id": "call_1",  "content": "{\"temperature\": \"21C\"} "}That full conversation goes back to the model in a second request. Only then does it write a plain reply describing conditions in Lisbon. Nothing about the temperature came from training data. It came from a live source, routed through a function the developer controlled entirely.Also Read: Muse Glimmer: Complete Guide to Meta’s Open Agentic AI ModelWhere It Breaks DownFunction calling is not free of tradeoffs. High-throughput workloads that need thousands of requests per minute pay a cost for every extra round trip a tool call adds. Creative tasks, like writing or brainstorming, gain nothing from tools built for retrieval and computation. Models can also select the wrong function or fill in plausible but inaccurate arguments, which makes validation on the receiving end a requirement, not an option.Strict mode reduces this risk with constrained decoding at the token level rather than checking output after the fact, forcing every argument to match the schema exactly. Even so, it does not remove the need for the application to verify what comes back before acting on it.Also Read: OpenAI Agents SDK: A Complete Guide for Developers\Final ThoughtFunction calling establishes the pattern: a model requests an action, and an application decides whether to grant it. That pattern has quietly become the invocation layer underneath a larger shift, the move toward standardized protocols like MCP, which extend the same idea by letting a single tool definition work across different models and providers.The mechanics here will likely stay stable even as the surrounding ecosystem changes shape. That core pattern is what makes any of this safe to build on.You May Also Like:White House Calls OpenAI, Google, Meta for AI Safety MeetingOpenAI Faces Another Senior Exit as COO Brad Lightcap Departs Amid IPO BuzzOpenAI Launches GPT-5.6-Cyber as Daybreak Adds Blue and Red Access TiersFAQs1. What is OpenAI function calling?OpenAI function calling allows a model to request a specific function or tool with structured arguments. The application then executes that function and returns the result to the model for a final response.2. How does OpenAI function calling work?The process typically involves five steps: the user sends a request, the model selects a tool, the application executes it, the result is returned to the model, and the model generates the final response.3. Does the OpenAI model execute functions itself?No. The model generates a tool call, but the application or backend executes the actual function. This keeps databases, APIs, credentials, and business logic under the developer's control.4. What is the difference between function calling and Structured Outputs?Function calling allows a model to request an action, such as querying an API or database. Structured outputs ensure that the model's response follows a defined data format, such as a specific JSON schema.5. What can OpenAI function calling be used for?Function calling can connect AI applications to databases, weather services, APIs, calculators, customer-support systems, inventory platforms, scheduling tools, and other external services.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Phantom Blade Zero is heading to PC on October 29, 2026. The action game is also coming to PS5 on the same day. S-GAME is behind the title, which combines fast sword fights with a dark world inspired by Chinese martial arts and action movies.The PC version is already drawing attention, as players want to know if their current systems can handle it. The game runs on Unreal Engine 5 and features detailed environments, quick combat, and more than 30 weapons. These features could make it a demanding game to run at 60 FPS.The full PC requirements haven’t yet been confirmed, but the Epic Games Store page listed the required features. The game requires Windows 10 or Windows 11 (64-bit) as the operating system. The game requires an Intel Core i7-8700K or AMD Ryzen 5 3600 as the minimum processing requirement. Similarly, the game requires an NVIDIA GeForce GTX 1660 6GB or an AMD Radeon RX 5500 XT 8GB as the minimum GPU requirement. However, if players want better performance, the Intel Core i5-10600K or AMD Ryzen 5 5600X would be their best choice. For graphics cards, they need an NVIDIA GeForce RTX 3060 Ti 8GB or an AMD Radeon RX 6700 XT 12GB. However, in all cases, 16GB of RAM is mandatory. Phantom Blade Zero looks like a game that will need a decent gaming PC. Its fast fights and detailed visuals could put extra pressure on older hardware. Currently, the listings show that the game will cost Rs. 4,299 on PC and PS5 for the Standard Edition, and Rs. 5,199 for the Digital Deluxe Edition. Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Rajasthan Royals has clarified that ChatGPT did not independently discover Vaibhav Suryavanshi during IPL 2026. AI supported the scouting process alongside data, scouts and cricket experts.RR COO Alok Chitre explained the process during a Hindustan Times discussion with RR technology leaders and OpenAI India. The franchise combined AI tools with traditional scouting to spot young talent.Chitre confirmed technology played a role in finding Suryavanshi, while human judgment remained important. “Part of it? Yes,” Chitre said when asked whether AI helped identify the young batter.RR uses technology to study large amounts of cricket data more quickly. The system can help teams spot player patterns and performance details during scouting.Scouts still watch players closely before the franchise makes important decisions. Coaches also bring experience and cricket knowledge that AI cannot fully measure.Rajasthan Royals uses AI for several other parts of its IPL operations. These areas include auction planning, ticket sales, fan engagement and content creation.The franchise also held a GenAI hackathon before an auction. Participants created models that suggested possible 25-player squad combinations for Rajasthan Royals.RR later used some recommendations from the event during its planning process. The experiment showed how AI can support auction decisions without replacing management.The franchise also uses AI agents to study ticket sales and stadium occupancy. These tools can help identify empty sections and changing demand during matches.RR has also created an in-house GenAI studio for content production. ChatGPT helps create photoshoot ideas and visual concepts for commercial campaigns.OpenAI and Rajasthan Royals both support a human-led approach to AI. Technology can process information quickly, while cricket experts make the final calls.Suryavanshi’s story shows how modern scouting is changing. AI can help find useful patterns, while scouts still bring instinct, experience and cricket knowledge.Also Read: Gemini Hits 1 Billion Users: Can Google AI Beat ChatGPT?Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

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An income tax notice can unsettle taxpayers after they file their returns. However, many communications involve routine checks, missing details or mismatched records.The department may request a correction, supporting documents or payment of an outstanding demand. Each notice serves a different purpose and requires a specific response.Routine Mismatches Can Trigger NoticesThe Income Tax Department compares returns with AIS, TIS and Form 26AS. These records help officials check income, deductions, transactions and tax credits.Form 26AS primarily contains TDS and TCS details. Meanwhile, AIS provides wider information, including interest income and reported financial transactions. Taxpayers can also challenge incorrect information through the AIS feedback facility.Vipin Upadhyay, partner at King Stubb & Kasiva, said, “Income tax notices should not necessarily be viewed as an indication of wrongdoing.” He described them as part of the tax verification process.A Section 143(1) intimation communicates the outcome of return processing. It may confirm a refund, report no additional liability or create a tax demand.The department may also propose adjustments for calculation errors or unsupported deductions. Taxpayers should compare the intimation with their ITR, AIS, Form 26AS and payment records.A Section 139(9) notice identifies a defective return. Missing information, inconsistent figures or an income and TDS mismatch can trigger this communication.Taxpayers must correct the listed defect within the given period. Otherwise, the department may treat the return as invalid. AY 2026-27 proceedings follow the Income-tax Act, 1961.Scrutiny Notices Need Detailed RecordsA Section 142(1) notice asks for information, documents or clarification. The assessing officer may request bank statements, investment details, deduction proofs or transaction records.Taxpayers should answer every question separately. They should attach only relevant documents and keep copies of each submission.A Section 143(2) notice concerns scrutiny assessment. The department uses this process to examine selected parts of an ITR more closely.A scrutiny notice alone never proves tax evasion. Still, taxpayers must support the figures reported in their returns. Relevant records may include salary documents, invoices, property papers and foreign-income statements.Section 148 covers income that may have escaped assessment. Taxpayers should check the assessment year, disputed transaction and deadline before replying.Reassessment cases can involve complex records or legal questions. A chartered accountant or tax lawyer may help when the disputed amount is large.An outstanding demand may arise from a TDS mismatch, interest calculation or earlier adjustment. Taxpayers should compare the demand with tax challans and filed returns.Section 245 permits authorities to adjust a refund against unpaid tax. Authorities must send a written intimation before making that adjustment.How Taxpayers Should RespondTaxpayers should authenticate every income tax notice before responding. The e-filing portal allows verification through the Document Identification Number or PAN and notice details.The department generally treats communications without a DIN as invalid, subject to permitted exceptions. Taxpayers should avoid replying through unofficial links or sharing login details.After verification, taxpayers should review the section, assessment year, questions and response deadline. They should then reconcile the ITR with AIS, TIS, Form 26AS and bank records.A clear response should address each issue and include supporting evidence. Unrelated documents can make the submission difficult to review.The e-Proceedings service allows taxpayers to view notices, upload documents and submit responses online. Outstanding demands appear under the “Pending Actions” section.Taxpayers should retain the notice, response, attachments and electronic acknowledgement. Timely action can prevent a routine discrepancy from developing into a larger compliance dispute.Also Read: India's New Tax Amendment Bill: Everything Businesses Need to Know Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Overview:Spot Bitcoin ETFs recorded $131.13 million in daily net outflows, with ARKB seeing the largest single-day withdrawal at $58.82 million.The White House is reportedly preparing an Aug. 19 meeting around crypto and the CLARITY Act.Trezor disclosed a third-party breach affecting 13,689 customers, while Solana’s Alpenglow upgrade targets roughly 150 ms finality.The crypto markets saw major developments as spot Bitcoin ETFs recorded $131 million in net outflow, while XRP Ledger added around 490,000 new accounts in the first half of the year. Also, the White House is planning a meeting about the CLARITY Act and Trezor data was breached, leaking email addresses and phone numbers of users.Bitcoin Witnessed $131 Million in OutflowsAccording to SoSoValue, yesterday spot Bitcoin ETFs had a total net outflow of $131.13 million. The spot Bitcoin ETF with the largest single-day net inflow yesterday was Grayscale Bitcoin Mini Trust ETF BTC, with a single-day net inflow of $38.9268 million. Next was Morgan Stanley ETF MSBT, with a single-day net inflow of $7.0806 million; MSBT’s historical total net inflows have reached $436 million. The spot Bitcoin ETF with the largest single-day net outflow yesterday was Ark Invest and 21Shares’ ETF ARKB, with a single-day net outflow of $58.8155 million; ARKB’s historical total net inflows have reached $1.277 billion. The total net asset value of spot Bitcoin ETFs was $77.271 billion, the ETF net asset ratio reached 6.07%, and cumulative historical net inflows have reached $51.846 billion.XRP Ledger Adds Nearly 490,000 AccountsXRP Ledger added 489,739 accounts during the first half of 2026, pushing its total to about 8.4 million as Ripple’s RLUSD stablecoin and broader financial applications expanded across the network. Public XRPL data shows wallet creation remained strong during the six months, giving the blockchain another measure of growth as it seeks to expand beyond its traditional role in XRP payments and transfers. Ripple’s dollar-backed stablecoin has become part of XRPL’s expanding payments infrastructure, creating additional reasons for individuals, exchanges, applications and businesses to establish accounts on the ledger.Stablecoins can generate different network activity from speculative crypto trading. Also Read: XRP On-Chain Metrics Explained: 7 Signals Investors Should WatchWhite House Plans Meeting Over CLARITY ActThe White House has reportedly planned an Aug. 19 meeting with crypto and prediction market executives as Polymarket traders place the CLARITY Act’s 2026 passage odds at 21%.Politico reported on Aug. 13 that the White House is expected to host executives from the crypto and prediction market sectors on Aug. 19, citing people familiar with the planned gathering. According to the report, the White House has not disclosed a formal agenda or released a list of participants. Executives from traditional financial companies may also attend, while it remains unclear whether President Donald Trump will take part. Trezor Data BreachTrezor warned 13,689 customers that their personal information was exposed after an unauthorized actor breached systems belonging to fulfillment provider ShipMonk.The hardware wallet maker said ShipMonk notified it on Aug. 10 after discovering unauthorized access to systems containing customer order data. Trezor’s own infrastructure, devices and wallet backups were not compromised.The incident affected customers in the United States, United Kingdom, Sweden, Colombia, Brazil, Italy and Portugal. Of those affected, 11,742 had their names, email addresses, phone numbers and shipping addresses exposed. Another 1,947 customers had names, cities and email addresses compromised.Alpenglow Upgrade Targets 150 ms FinalitySolana plans to replace TowerBFT with Alpenglow, targeting roughly 150 ms finality and expected to activate with Agave 4.3, currently targeted for October 2026. Alpenglow code is included in Agave 4.2 for testing but will not activate on mainnet until Agave 4.3. Agave 4.2 (stable 4.2.0 released Aug. 7; 4.2.1 pre-release Aug. 13) will also reduce slot times from 400 ms to 200 ms in four 50 ms steps starting the week of Aug. 17. Alpenglow replaces TowerBFT with Votor, removes on-chain vote transactions, uses BLS aggregation, and expects a 1.6 $SOL validator admission ticket per epoch. The governance vote passed with 98.27% support in Sept. 2025; an Alpenglow bug bounty (up to 50,000 SOL) runs Aug. 5-19. Also Read: Ethereum Price Prediction 2026: What Google Gemini Forecasts for ETH FAQs:1. How much did Bitcoin spot ETFs lose in daily flows?US spot Bitcoin ETFs recorded about $131.13 million in net outflows. ARKB led withdrawals with roughly $58.82 million, while Grayscale’s Bitcoin Mini Trust recorded the strongest inflow.2. How much did XRP Ledger grow in the first half of 2026?XRPL added 489,739 new accounts during H1 2026, taking its total to around 8.4 million. Growth has coincided with expanding payments, stablecoin and financial use cases.3. What happened in the Trezor data breach?A breach at fulfillment provider ShipMonk exposed customer information linked to 13,689 Trezor users. Trezor said its own wallet infrastructure, devices and backups were not compromised.4. What is the White House meeting about?The White House is reportedly planning an Aug. 19 meeting with crypto and prediction-market executives. The agenda has not been formally disclosed, but the CLARITY Act is a key policy focus.5. What is Solana’s Alpenglow upgrade?Alpenglow is designed to replace TowerBFT and target roughly 150 ms finality. It is expected to activate with Agave 4.3, currently targeted for October 2026.

Researchers at the National Institute of Standards and Technology (NIST) have developed a chip-scale optical isolator that achieves 30 dB peak isolation without using magnetic materials. The device is built on a silicon nitride and thin-film lithium niobate platform and is designed to work with standard semiconductor manufacturing processes.The magnet-free isolator achieves 30.6 dB ± 0.1 dB peak isolation at 789.7 nanometres. It maintains more than 24 dB isolation across a 30-nanometre bandwidth spanning 770 nm to 800 nm and can isolate two lasers simultaneously with more than 20 dB isolation within a 10-nanometre window, without heater adjustment.How NIST Isolator WorksOptical isolators work like one-way valves for light. They allow forward-propagating photons to pass while blocking backward reflections that can destabilize lasers, corrupt signals, and introduce noise in sensitive photonic integrated circuits.Conventional optical isolators typically rely on the Faraday effect and bulk magneto-optical materials. These materials are difficult to integrate with standard silicon-based microfabrication.The NIST team instead uses radio-frequency electro-optic modulation to create synthetic motion. The approach uses time-periodic phase modulation to cancel backward-propagating light while allowing forward light to pass.At its core is a four-channel Mach-Zehnder modulator that splits incoming light into four parallel interferometric paths. Each path is phase-modulated by radio-frequency waves applied through a gold coplanar waveguide beneath a 150-nanometre thin-film lithium niobate layer, bonded onto 350-nanometre silicon nitride waveguides.6.5 GHz RF Drive and 32 mW PowerThe device uses a 6.5 GHz base frequency, with a third harmonic at 19.5 GHz. About 32 mW of RF power is delivered to the device, significantly below the watt-level drive levels required by earlier traveling-wave isolator approaches.Six chromium microheaters tune the power balance and relative phase between the four channels. This allows the system to maintain the required interference conditions.The measured forward-to-backward peak-spectrum power ratio reached 30 dB, with maximum isolation of 30.6 dB ± 0.1 dB at 789.7 nm. The researchers also measured an excess insertion loss of 0.023 dB ± 0.018 dB under fixed heater bias, a variation that is statistically indistinguishable from zero.Also Read: AI Translator Headphones: How Real-Time Language Translation WorksDesigned for Atomic Clocks and Quantum SensorsThe 770-800 nm operating range covers important rubidium-87 transitions, including the D2 line at 780.2 nm, the D1 line at 794.8 nm, and the two-photon transition at 778.1 nm, as well as potassium-39 resonances.These wavelengths are relevant to chip-scale atomic clocks, quantum sensors, laser cooling systems, and atomic spectroscopy. The technology could also be adapted to telecommunications wavelengths by redesigning the passive splitters and combiners.Foundry Compatibility Could Enable Mass ProductionThe isolator uses heterogeneous integration, with a thin-film lithium niobate layer bonded onto silicon nitride. A 100-millimeter wafer can accommodate nine chips, each 22 by 20 millimeters, with 171 isolators in total.The NIST team said the approach provides a route towards mass-produced photonic integrated circuits using standard semiconductor infrastructure. The work was developed through the NIST-on-a-Chip program, funded by the US Department of Commerce through awards 70NANB23H104 and 70NANB23H105.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Overview:Discover the four categories hidden among 16 seemingly unrelated words.Use hints featuring Bumblebee, Echo Chamber, India Ink, and Google Drive to narrow down the groups.Check the complete answers and previous Connections solutions from August 9 to 13, 2026.The NYT Connections August 14 grid is now live, offering players a new challenge. Words like Wolverine, HiveMind, Deep Pen, Google Drive, Bubble, etc., make no sense at first glance. To conclude and identify themes such as ‘black and yellow,’ ‘like-minded people,’ ‘comic book writers,’ and ‘triangle logos,’ players need to take a careful look at the grid. The world of word puzzles is massive, but hardly any others compete with the puzzles that The New York Times presents. Whether it's Strands, Connections, or Wordle, each of these web-based word puzzles has its specific word-guessing method. In NYT Connections, the theme isn’t stated initially, but once players guess the right sets, the game reveals the themes:Hints for August 14, 2026This puzzle is tricky, but some clues may make things easier for gamers. Here are some hints to help players solve today’s puzzle. Let's start with the hints category-wise:Easiest Group (Yellow): Today’s yellow group words offer a glimpse into the world where characters are all in black and yellow.Moderate Group (Green): Do you watch a lot of science fiction movies? These are the places where people think in a similar manner.  Challenging Group (Blue): If you are a comic book fan or create your own comic stories, you must have heard about these tools.  Most Difficult Group (Purple): Finally, the purple category words are all logos, but they have a particular shape. One Word Hints For Today’s PuzzleIf you are still a bit confused about the themes of today’s puzzle, below are the one-word hints. From every category, one word is listed below:BUMBLEBEEECHO CHAMBERINDIA INKGOOGLE DRIVEThese one-word hints will help you identify what other words of the category may contain. Answers for August 14, 2026The hints should have resolved the confusion and helped players form the groups with fewer errors. However, if that’s not the case and some are still trying to figure out today’s word groups, here are the solutions to the NYT Connections of August 14, 2026. Yellow Category (BLACK-AND-YELLOW): BUMBLEBEE, CAUTION TAPE, CHARLIE BROWN, WOLVERINEGreen Category (PLACES WHERE EVERYONE THINKS THE SAME WAYS): BUBBLE, ECHO CHAMBER, HIVEMIND, SILOBlue Category (COMIC BOOK ARTIST'S TOOLS): BRISTOL BOARD, DIP PEN, INDIA INK, STRAIGHT EDGEPurple Category (TRIANGLE LOGOS): BASS ALE, CITGO, DELTA AIRLINES, GOOGLE DRIVEThese are the four categories for today’s puzzle, and congratulations to those who have solved it without any help. Also Read: Today’s NYT Strands Hints, Answers for August 13, 2026 (Puzzle #893)Check out the image below to know how to make the sets of today’s puzzle:Previous Answers (August 9-13) Final WordsThe August 14 edition of NYT Connections offers players a satisfying mix of everyday iconic characters, science fiction references, and clever wordplay. What begins with familiar character appearances and science fiction references gradually evolves into subtler patterns, especially in the ‘logo’ phrases.  This steady progression in difficulty is what makes today’s grid feel rewarding rather than frustrating. Overall, today’s challenge is a reminder of why Connections continues to stand out as one of the most engaging daily brain teasers.Also Read: NYT Connections Hints, Answers for August 13, 2026 (Puzzle #1159)Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Professional certification has become an important step for people who want to grow in competitive industries. Whether someone is entering finance, technology, healthcare, or another specialized field, exams often serve as a gateway to better opportunities. At the same time, the way people prepare for those exams has changed dramatically. Digital learning tools now make it easier for busy professionals to study with structure, flexibility, and clearer feedback than traditional methods often provided.Using Specialized Study Materials to Build a Strong FoundationFor people beginning a new career, let’s say in securities, for example, preparation often starts with finding resources that explain complex ideas in a clear and organized way. Quality SIE study materials can help learners understand core financial concepts, industry terminology, regulations, and exam expectations before they move deeper into the licensing process.This matters because many candidates are balancing study time with work, school, family responsibilities, or career transitions. A structured digital prep option can help them focus on what they need to know instead of trying to piece information together from scattered sources. When the first stage of preparation feels manageable, candidates are more likely to stay consistent and confident as they move forward.Why Online Learning Works for Busy ProfessionalsOne of the biggest advantages of digital learning is that it respects the reality of modern schedules. Many people preparing for professional exams are not full-time students with open days to study in a classroom.They may need to review lessons during lunch breaks, after work, early in the morning, or while traveling. Online platforms make this possible by giving learners access to materials when they have the time and energy to focus. This flexibility can make a major difference for people who are motivated but need a study plan that fits into real life.Turning Complex Topics Into Manageable LessonsProfessional exams can feel intimidating because they often cover a wide range of technical information. Digital learning tools help by breaking large subjects into smaller lessons that are easier to absorb and review. Instead of reading dense material without a clear path, learners can move through content in a step-by-step sequence that builds understanding.Many platforms also use quizzes, practice questions, and progress tracking to help students see where they are improving and where they still need work. That kind of feedback can reduce frustration because candidates are not left guessing whether their study time is actually helping.Helping Learners Practice Before Exam DayPractice is, like, one of the most important parts of exam prep because it lets learners apply what they know in more realistic circumstances. A lot of digital tools offer practice exams, timed questions, and topic-based revision sessions that basically recreate the pressure of the actual test. That kind of practice can help candidates build stamina, get better at pacing, and spot weak spots before exam day is even close. It also makes people more at ease with the exam’s structure, and that can lower anxiety. If learners already know what to expect, they can put their focus into answering questions carefully instead of getting sidetracked by nerves. Building Confidence Through Better Progress TrackingAnother pretty big benefit of digital certification prep is being able to see progress as it happens. Rather than just guessing whether their study time is working, learners can check scores, completed lessons, wrong answers, and how they perform by subject. When tracking is done this way, candidates can choose smarter priorities, like where to spend effort, especially as exam day starts approaching. It also helps with confidence, because improvement becomes visible, even if the content still feels a bit demanding.Supporting Different Learning StylesNot everyone learns best by reading a textbook from start to finish. Some learners need visuals, some need repeat cycles, and others prefer to hear explanations before the material finally “clicks.” Digital learning platforms can help with that by combining written lessons, videos, flashcards, quizzes, and interactive exercises. Offering these different routes helps learners connect with the information in a way that fits how they actually process it. A more personalized study journey can, overall, make practice feel less generic and more usable. A more personalized study experience can help learners stay consistent, even when the topics feel tricky, and it keeps them engaged longer than a single style might.Preparing for the Future of Career DevelopmentDigital certification prep is not just changing how people study for one exam. It is also reshaping how professionals think about long-term career growth. As industries evolve, workers need ways to keep learning without putting their lives or jobs on hold.Online education gives people a practical path to gain credentials, sharpen skills, and move toward new roles with more confidence. For candidates preparing for finance-related exams or any other professional milestone, digital tools can make career development feel more accessible, organized, and achievable.

Rare coins have drawn collectors in for generations, and over time they've earned a spot in serious long-term investment conversations too. They're tangible in a way stocks and mutual funds simply aren't — pieces of history with a fixed, limited supply and an appeal that doesn't fade with the news cycle. No investment comes with guarantees, of course, but quality rare coins have shown real staying power, largely because demand for them isn't confined to financial markets alone. Collectors buy them out of passion. Historians buy them for what they represent. Investors buy them for both reasons at once. That mix of motivations is part of what makes rare coins worth a second look for anyone trying to diversify beyond the usual assets.Understanding Where Rare Coins Fit Into Your PortfolioA question a lot of people wrestle with early on is where to invest your money as they put together a balanced financial strategy. There's no single right answer — it comes down to your goals, how much risk you're comfortable with, and how long you're willing to hold. Rare coins aren't meant to replace a retirement account or a diversified stock portfolio. Think of them instead as an alternative asset, something that adds texture to a plan rather than anchoring it. Their value doesn't track the stock market's daily swings; it moves with rarity, historical weight, physical condition, and how badly collectors want a particular piece.What draws a lot of investors in is simpler than any of that, though: rare coins are something you can actually hold. They aren't a line item on a screen or a fractional share in a company you'll never visit. A well-chosen collection preserves a slice of history while it sits there quietly appreciating. And as with any investment, doing the homework pays off. Getting familiar with grading standards, authentication practices, and how the market tends to move helps buyers make real decisions instead of gambling on a hunch.Scarcity Helps Create Long-Term DemandLimited supply is arguably the single biggest reason rare coins hold their appeal decade after decade. Surviving examples often become harder to find, not easier, as years pass — collections get locked away for generations, and individual coins quietly disappear from circulation for good. That steady erosion of supply is exactly what keeps demand from collectors and investors alike so resilient.Take the Indian Head gold coin as an example of why certain pieces command such strong prices. It's a well-known chapter of American numismatic history, prized for its distinctive design, its scarcity in higher grades, and the collector interest that's never really let up. You'll find that same combination — history plus genuine rarity — running through plenty of other respected coin series as well.Condition matters just as much as scarcity. Professional grading organizations assess coins against standardized criteria, giving buyers a consistent way to judge quality and confirm authenticity. Even a small shift in grade can swing a coin's desirability considerably, which is exactly why experienced investors lean toward certified pieces rather than anything unverified.History Gives Rare Coins Lasting AppealTrends come and go, but rare coins tend to carry a kind of historical weight that doesn't age out. A single coin might capture a pivotal moment in a nation's story, commemorate something significant, or preserve artistry that simply can't be reproduced today. Buyers respond to that for reasons that go well beyond return on investment.That historical pull also widens who's actually in the market. Museums, dealers, collectors, and investors are all buying and selling at once, and that variety is part of what keeps demand steady — it isn't riding on any one type of buyer showing up. Plenty of people start out collecting simply because they love history, then later realize they've quietly built something with real financial value.Education is still one of the biggest edges a new investor can have. Digging into mintage figures, historical records, grading standards, and population reports is how you tell truly scarce coins apart from ones that just look old. More often than not, that kind of knowledge beats chasing whatever's trending.Patience Often Rewards Careful InvestorsRare coin investing was never really built for quick wins. It rewards patience and a disciplined approach to buying far more than it rewards speed. Investors who prioritize quality over quantity tend to end up with collections that hold their appeal for years, and that mindset also makes it easier to sit still when the market gets noisy in the short term.Working with reputable dealers, insisting on certification from respected grading services, and storing coins properly are all part of protecting that investment. A coin that's been kept in good condition will almost always outshine one that's been mishandled or, worse, cleaned — cleaning a rare coin is one of the fastest ways to strip away its value, since collectors generally want original surfaces, not polished ones.Diversification still matters here too. Even someone who's fully convinced of a rare coin's value shouldn't pour every available dollar into one asset class. Pairing traditional investments with a carefully chosen collectible or two builds a strategy that can hold up no matter what the broader market is doing.Building Wealth With a Long-Term PerspectiveRare coins keep attracting attention because they bring together history, craftsmanship, scarcity, and something you can physically hold — a combination few other investments can match. They ask for research, patience, and realistic expectations in return, but for those willing to put in the work, they can become a genuinely worthwhile piece of a diversified portfolio. No asset performs identically every year, but rare coins have earned a reputation for staying relevant across generations regardless. For investors who care about financial opportunity and historical significance in equal measure, rare coins deserve serious consideration — not as a shortcut to fast returns, but as one thoughtful piece of a long-term plan.

Gold traded lower on MCX on August 14 amid a higher US dollar and 10-year bond yields, despite the US inflation data for July easing expectations of a rate hike by the US Federal Reserve in September. August gold futures fell 0.66% to Rs. 1,52,449. September silver futures declined 0.99% to Rs. 2,33,106. Meanwhile, Brent crude futures rose 0.08% to $87.14 per barrel. US West Texas Intermediate (WTI) edged lower by 0.14% to $81.36 per barrel.Domestic Gold Prices24K gold fell by Rs. 71 to Rs. 1,52,890 per 10 grams, while 22K gold also declined by Rs. 65 to Rs. 1,40,150. By city, Mumbai and Kolkata mirrored prices at Rs. 1,52,890, while Delhi was at Rs. 1,53,040, and Chennai at Rs. 1,53,170.US Gold PricesUS gold prices slipped on Friday as investors locked in profits after mild US inflation data pushed bullion to its highest level in more than two months and weakened the case for a near-term Federal Reserve ​rate hike. Spot gold was down 0.5% at $4,326.75 per ounce. US gold futures for December delivery fell nearly 1% to $4,382.50.Spot ⁠silver slipped ​0.4% to $64.17 per ounce. Platinum slipped 0.3% to $1,711.84, while palladium ​was steady at $1,306.98.Also Read: Nifty-Gold Ratio Falls to 1.6: Is India’s Stock Market Rally About to Begin?Key Levels to Watch"There is some episodic and more speculative capital that's maybe ​taking a bit of profit in gold, because there's not a near-term catalyst quite so potent immediately in front of us," said Ilya Spivak, head of global macro at finance content network Tastylive. "Gold may be setting ​up, with some choppy trading along the way, for a meaningful rally now. And if ​we can take out $4,400, I don't think $5,000 by year-end is any kind of a stretch."On MCX, gold faces resistance near the falling trendline around Rs. 1,56,000 and witnessed profit booking, with prices now finding immediate support near Rs. 1,52,600. A sustained break below this level could extend the correction towards Rs. 1,50,000. However, the broader structure remains constructive as prices continue to trade above key EMAs.

Zelda Fans, Something Big May Be Coming! - A reported ESRB listing clue has sparked fresh speculation about a possible Ocarina of Time release for Nintendo Switch 2.Ocarina of Time - The Legend of Zelda: Ocarina of Time remains one of the most celebrated games in the franchise.An Unexpected Rating Clue - A reported ESRB-related discovery has fueled speculation about a Switch 2 version.Why Switch 2 Matters - Nintendo's newer hardware could give a classic Zelda adventure a technical refresh.Great Fairy Redesign Rumours - The biggest talking point is speculation that the Great Fairy character could receive a visual redesign.Perfect Timing for Zelda - The speculation arrives as Nintendo fans look ahead to The Legend of Zelda's 40th anniversary.What Could Nintendo Be Planning? Fans are debating whether the rumored project could be a port, remaster, or another enhanced release.Zelda Fans Want More - A Switch 2 version could attract both longtime Zelda players and a new generation.Don't Call It Official Yet! The reported clues have sparked excitement, but Nintendo has not officially confirmed the rumored release.Read More StoriesJoin our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp

Banking’s technology problem is often described as a race toward intelligence. More automation. More AI. Faster decisions. Smarter workflows. But many of the industry’s weakest points remain surprisingly familiar. Capgemini found that financial institutions still face significant inefficiencies in core business functions, with customer onboarding and KYC — Know Your Customer — among the most inefficient processes; for banking, the report also flags cross-border payments and compliance management among the top pain points.To understand why modernization in banking so often becomes difficult at the point of execution, we turn to Jayanth M. Prasanna, a global quality engineering lead whose work has helped financial institutions modernize some of their most sensitive operational systems without compromising stability, compliance, or day-to-day continuity. Across the modernization of customer verification (KYC) and anti-money-laundering systems (AML systems), sanctions-screening infrastructure, SWIFT-related change programs, and cross-border deal workflows, his work has made it possible for organizations to replace outdated architecture, reduce reliance on manual processes, strengthen release confidence, and bring greater consistency to systems where errors can carry regulatory and operational consequences.Jayanth, many programs still stall once they move from strategy into real operations. In your experience, what modernization programs move from strategy into real operations, what part do institutions most often underestimate?Many institutions still approach modernization as if it were mainly a feature question. They ask how to make systems faster, more intelligent, or more efficient. Those are valid goals. But in banking, the deeper issue is whether the system remains dependable when the conditions are less than ideal.A workflow may perform well in a controlled environment and still create serious problems in production. In regulated operations, the real pressure comes from incomplete data, overlapping rules, exception handling, audit expectations, and timing. That is why I think banks often underestimate the difference between a system that is technically upgraded and one that is truly ready to be trusted. Modernization becomes meaningful only when it strengthens control, not when it simply adds capability.You raised user interface automation coverage in a major banking modernization program and led the migration of a mission-critical compliance platform to Angular. What kinds of dependency or logic problems usually become visible only once the migration is underway?The first thing that becomes visible is how much business logic is embedded in the platform beyond what the front end seems to show. A compliance system may look like a workflow with forms, validations, and analyst actions, but underneath that there are years of accumulated decisions. Rules around onboarding, due diligence, escalation, exception handling, and downstream integrations are often more interconnected than the business initially realizes.Once migration starts, those connections become very difficult to ignore. A change that looks straightforward from a technical perspective can affect how a customer record is validated, how an analyst handles an incomplete case, or how a compliance decision is documented and defended later. That is why these programs have to be approached as workflow migrations, not just technology upgrades. The issue is usually not whether a page renders correctly in the new stack. The issue is whether the logic, control path, and case behavior still hold together once real users and real data start moving through the system.Leading the implementation and validation of SWIFT messaging and payment platforms at a commercial bank, you reduced transaction errors, improved system reliability, and supported mandatory annual SWIFT upgrades. Once a bank has technically established the connection, where do international payment processes most often begin to break down in practice?Usually, after the message leaves the point of connection and starts moving through the wider process. A bank can confirm that a SWIFT interface is up, that a message format is supported, and that the annual upgrade was completed. That does not automatically mean the payment process is stable.The real failure points are usually downstream. Routing logic may behave inconsistently in certain scenarios. Data can lose quality as it moves between systems. Exceptions may not be surfaced early enough for teams to act before a delay becomes material. Reconciliation may become more difficult if message handling is technically valid but operationally fragile. In international payments, that is where readiness is tested. Not at the point where the connection succeeds, but at the point where the institution has to keep data accuracy, exception handling, and traceability intact all the way through the transaction lifecycle.Financial firms are trying to scale AI while still struggling with fragmented workflows, weak data quality, and control discipline. In a banking environment, what usually prevents an advanced tool from scaling once it meets those conditions?The biggest barrier is that AI depends on process quality more than many institutions expect. If the underlying workflow is inconsistent, if the ownership of key decisions is fragmented, or if the data path is unreliable, then the tool inherits those weaknesses very quickly.In banking, that creates a particular problem because advanced systems are often introduced into environments where exception handling, auditability, and accountability already matter a great deal. If the institution cannot clearly explain how a decision was reached, where the source data came from, or how a case moved through review, then scaling intelligence becomes difficult. The technology may appear promising in a controlled setting, but once it enters a live regulated process, the lack of structured inputs and governed execution becomes a limiting factor. In that sense, AI does not remove process weakness. It exposes it faster.As Quality Engineering Lead for the New York operations of a major international commercial bank, you enabled uninterrupted OFAC-compliant screening, full audit traceability, and continuity across high-risk U.S. banking operations. How did you make that transition work when the bank moved from a legacy sanctions platform to Firco Trust?The first step was to treat the project not as a simple platform replacement, but as a controlled transition inside a highly regulated environment. I led the replacement of an obsolete sanctions platform with Firco Trust, and that meant the priority was not only getting the new system live. It was making sure screening integrity, traceability, and business continuity were preserved throughout the change.That required close attention to the workflows that could not break. We validated customer and PEP screening in detail, made sure legacy data was migrated accurately and securely into Firco Trust, and tested the new case-management capabilities for both functionality and operational reliability. I also directed user acceptance testing across environments so stakeholders had enough evidence to approve release decisions with confidence. Just as important, we kept the process tightly coordinated across product, engineering, and business teams. Defects had to be resolved quickly, release risk had to be assessed continuously, and audit traceability had to remain intact from the old environment to the new one. That is what made it possible to modernize a high-risk sanctions workflow without losing control of the screening process while the transition was still underway.More recently, you gave the business greater traceability, clearer governance, and a more reliable way to manage complex cross-border workflows by replacing fragmented Excel-and-email approval chains with a more centralized process. What does a business gain once manual approval chains are pulled into a structured system?First of all, it’s visibility. Not visibility in a reporting sense, but visibility into the process itself. Once approvals move out of spreadsheets and email threads and into a structured system, the business can see who acted, what was approved, which version is current, where a delay entered the workflow, and how the decision path can be traced later.That matters because manual approval chains often feel manageable right up until the process becomes multi team, multi region, or audit sensitive. Then the weakness is no longer just an inconvenience. It becomes uncertainty. Teams start spending time reconstructing decisions instead of advancing the work. A structured workflow changes that. It gives the business a reliable approval lineage, clearer accountability, and a better understanding of where the process is slowing down. Before it improves scale, it improves visibility. And in complex financial workflows, that is usually the condition that makes scale possible.Your approach has centered on identifying risk early and deciding whether a platform is genuinely ready for production. Before a major release in a regulated banking system, what evidence do you need to see before you are comfortable saying the platform can be trusted in production?In practical terms, it means asking difficult questions before release instead of after an incident. Which business flows carry the most risk? Which dependencies are likely to fail first? What evidence is needed before the team can say the platform is ready? What happens if the data is incomplete, the rule logic conflicts, or the exception volume rises?That changes the role of quality engineering. It stops being a final checkpoint and becomes part of risk control. The goal is not simply to document defects. It is to understand whether the institution has enough evidence to rely on the system in production.In highly regulated environments, that difference matters. The cost of uncertainty is higher.You have led global teams of up to 27 professionals and supported release decisions across regions. When timelines tighten and stakeholders want to move forward, how does a strong quality organization help leadership make a realistic release decision instead of an optimistic one?A serious quality organization creates clarity. It helps leadership understand what is known, what is uncertain, what is acceptable, and what creates real risk. A weaker organization may produce a lot of reporting, but still leave the business unsure about readiness.That difference becomes especially visible near major releases. When timelines tighten, can the team identify the issues that actually matter? Can it explain dependencies clearly? Can it help the business make a realistic decision, not just an optimistic one?If it can, then quality is serving the institution. If it cannot, then a lot of activity may be happening without much real control.Looking ahead, what will distinguish the banks that scale safely from the ones that keep introducing new instability?The institutions that scale safely will be the ones that build discipline into the operating model before they build more complexity on top of it. They will understand their data paths, reduce unnecessary workflow fragmentation, make release evidence reusable, and treat observability as part of the system rather than as an afterthought.They will also be more honest about dependencies. In banking, many failures do not come from a lack of ambition. They come from trying to layer new capability onto processes that are still difficult to see, govern, or explain. The banks that move forward successfully will not just adopt better tools. They will make their workflows clearer, their controls more measurable, and their production decisions more evidence based. That is what allows innovation to scale without creating a new layer of hidden risk underneath it.

Indian markets opened lower on Friday amid mixed global cues. Nifty 50 opened 33.95 points or 0.14% lower from its previous close of 24,361.90, while Bank Nifty declined 45.5 points or 0.08%. Sensex started 176.53 points lower at 77,903.4.Midcap and Smallcap both ended with modest gains, outperforming the benchmarks. The Indian rupee opened higher at Rs. 95.36 per dollar on Friday versus the previous close of Rs. 95.44.Domestic institutional investors (DIIs) bought net shares worth Rs. 4,353.09 in Indian equities on August 13, while foreign institutional investors (FIIs) turned net sellers, offloading equities worth Rs. 510.69.Sensex OutlookTechnically, the Sensex formed a small bearish candle, which indicates indecisiveness among traders.“We believe that the market has completed one leg of correction and is currently trading near an important support zone of the 20-day SMA. If it succeeds in trading above this level, it could bounce back to 78,500-78,700. On the flip side, if the index falls below 77,700, selling pressure is likely to accelerate. Below this level, it could slip to 77,400-77,200,” said Shrikant Chouhan, Head Equity Research, Kotak Securities.Nifty 50 OutlookThe Nifty 50 formed a small red candle on the daily chart with a short lower wick, while the long wicks from the last two sessions kinda suggest that fresh buy interest is showing up near the close.Nagaraj Shetti, Senior Technical Research Analyst at HDFC Securities, said, “The Nifty is holding above the crucial 24,300 support level, though the index has struggled to stick with gains. The broader trend looks mixed, with a slightly weak bias, and the 24,200-24,300 band is still the important support pocket. If the price keeps gravitating in this range, it could spark a bounce from lower levels. Meanwhile, 24,500 continues to act as the near-term resistance level.” Also Read: S&P 500 Hits Record High as Tech Stocks Rally and Oil Prices RetreatBank Nifty OutlookBank Nifty formed a small-bodied bearish candle on the daily chart and closed within the previous day’s trading range, reflecting indecision. The RSI is moving sideways, while the ADX remains flat, indicating a lack of strong directional momentum and volatility."Going ahead, the immediate resistance for Bank Nifty is placed in the 57,900-58,000 zone. Any sustainable move above this zone could result in Bank Nifty extending its pullback towards 58,400, followed by 58,800 in the short term. On the downside, the immediate support for Bank Nifty is placed in the 57,200-57,100 zone," said Sudeep Shah, Head of Technical and Derivatives Research at SBI Securities. 

Key Takeaways - AttaPoll gives research firms access to more than 2 million monthly active users across 70+ countries.Mobile surveys can deliver faster consumer feedback while rewards encourage participation.AI, respondent matching and mobile data can make future market research faster and more targeted.Digital market research has moved far beyond desktop questionnaires and email forms. Mobile survey apps now give research firms a direct route to millions of people through devices that remain close to consumers throughout the day. AttaPoll offers a clear example of this shift. The platform reports more than 2 million monthly active users across more than 70 countries. A January 2026 company profile also reported more than 40 million cumulative Android and iOS downloads and more than $40 million in rewards paid to users. Cint, a major research technology company, reported that AttaPoll had crossed $20 million in annual revenue.The wider research sector also shows strong scale. ESOMAR estimated the global insights industry at $142 billion in 2023, with 8% year-on-year growth. Such figures show the size of the market that mobile research platforms can serve.Smartphones Have Become Research ToolsThe smartphone has changed how people interact with brands, services and research studies. Kantar reports that more than 80% of survey participants complete surveys on mobile devices in many markets. The figure shows that mobile access now forms a central part of survey research rather than a secondary option. Kantar also recommends survey designs made for small screens, with short questions and simple layouts.SurveyMonkey's 2025 benchmark data offer another useful view. Mobile SDK surveys recorded a 34.37% response rate, while web-link surveys recorded 29.95%. SMS surveys reached 18.54%. These figures vary across research types and audiences, so they do not offer a perfect comparison. Still, they show strong potential for mobile-first research channels.AttaPoll Shows How the Model WorksAttaPoll connects consumers with market research opportunities through a mobile app. Users receive surveys that match their profile and can choose the frequency and length of studies. The platform also offers rewards after survey completion. Its current app listing describes a system that links users with market research companies and provides payment for completed surveys.This model creates a simple exchange. Research companies need consumer opinions. AttaPoll offers access to a large pool of respondents. Users receive rewards for their time. Brands then receive responses that can support product, advertising, pricing and customer research.The scale also matters. Cint reported more than 2 million monthly active AttaPoll users across more than 70 countries. A large respondent pool can help research firms find specific groups without the same level of manual recruitment that older research models often require.Faster Access to Consumer OpinionsTraditional research can take time to recruit participants, distribute questionnaires and collect enough responses. Mobile platforms can shorten that process. A researcher can reach an existing respondent pool and send relevant studies through an app.This model supports quick concept tests, brand checks, advertising research, product feedback and short consumer polls. It also supports repeated research. A brand can ask consumers about the same product at different stages rather than rely on one large study.The result creates a shift from occasional research toward regular consumer feedback. Mobile apps can make market research feel closer to a continuous information service than a one-time project.Also Read - Which AI Skills are Employers Looking for in 2027?Rewards Create a Stronger Participation ModelMoney and other rewards play a major role in mobile survey platforms. AttaPoll reports more than $40 million in rewards paid to users. That figure shows the financial scale of paid participation within its ecosystem.Rewards give consumers a direct reason to spend time on a survey. This approach also makes research more accessible to people who may not respond to unpaid questionnaires. Yet rewards can create a quality challenge. Some respondents may focus more on fast completion than careful answers.Research firms therefore need strong checks for rushed responses, repeated participation and unusual response patterns. A reward can attract attention, but good research still depends on thoughtful answers.Mobile Research Also Brings New RisksThe mobile model does not guarantee better data. Survey fatigue can reduce attention when users receive too many studies. Kantar recommends shorter surveys and warns against excessive survey frequency.Privacy also deserves close attention. AttaPoll's Google Play data-safety disclosure says the app may share personal information, app activity and app performance information. The listing also states that the app may collect location and personal information, while offering encryption during data transfer and a data-deletion request option.Such practices make trust a major part of digital research. Consumers need clear information about data use, while research firms need strong safeguards around sensitive responses.India Offers Strong Mobile PotentialIndia provides an important market for mobile research. A recent government survey reported that 85.5% of Indian households had at least one smartphone. The same survey reported 99.5% UPI use among surveyed youth.These figures create favorable conditions for app-based rewards and digital research. AttaPoll also has a dedicated India listing on Google Play, with more than 10 million downloads and roughly 360,000 reviews shown on the current storefront.Also Read - Why is Elon Musk Spending $16.8 Billion on AI ChipsThe Next Stage: AI, Mobile PanelsArtificial intelligence may add another major layer to this market. AI tools can help research teams create questionnaires, classify open responses, detect unusual patterns and summarize large datasets. Mobile respondent pools can then provide fresh human responses at scale.Research on AI-generated personas shows a more cautious picture. A 2026 study found that AI personas can match human response patterns for some stable questions but struggle with subjective and highly varied topics. Human respondents therefore remain important for research that needs genuine consumer experience and personal judgment.Mobile survey apps such as AttaPoll do not simply place old surveys onto smartphones. They create a faster connection between brands, research firms and consumers. With millions of users, large reward flows and broad geographic reach, this model gives digital market research a more immediate and continuous form. The next phase will likely combine mobile access, better respondent matching, stronger privacy controls and AI-assisted research tools. The core value will remain simple: fast access to real consumer opinions at a scale that traditional research models cannot always match.FAQs1. What is AttaPoll?AttaPoll is a mobile survey platform that connects consumers with paid market research surveys.2. How is AttaPoll changing market research?It gives research firms mobile access to a large pool of respondents and supports faster survey distribution.3. Why do mobile surveys matter for brands?Mobile surveys can help brands collect consumer opinions quickly across different markets and demographic groups.4. What are the main risks of mobile survey research?Key concerns include survey fatigue, sample bias, rushed responses, respondent quality and data privacy.5. Will AI replace human survey respondents?AI can improve survey creation and analysis, but human respondents remain important for genuine opinions, experiences and subjective judgments.Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp