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    Samsung Selects Chandigarh University Student as ‘Punjab AI State Topper’ | Web3Wire

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    Samsung Selects Chandigarh University Student as ‘Punjab AI State Topper’ | Web3Wire


    CU Student Devesh Panwar Wins Rs 1 Lakh Award for Developing AI-Based Document Search System

    CHANDIGARH, India, July 18, 2026 /PRNewswire/ — A Bachelor of Computer Applications (BCA) student of Chandigarh University, Devesh Panwar, has been named the “Punjab State Topper” in the Artificial Intelligence (AI) under the Samsung Innovation Campus (SIC) AI Program organised by Samsung in collaboration with Telecom Sector Skill Council (TSSC) and training partner Focal Skill Development (Focalyt) to equip Indian youth with industry-relevant in-demand skills in AI, loT, Big Data, and Coding & Programming, preparing them for future careers.

    A final-year student of Bachelor of Computer Applications (BCA) at University Institute of Computing (UIC) of Chandigarh University, Devesh Panwar also won a cash award of Rs 1 lakh along with a laptop, and exclusive Samsung rewards for achieving this remarkable milestone under the Samsung Innovation Campus AI Program.

     “Being named ‘AI State Topper’ was a moment of profound pride and validation for me. Hard work, intense technical training and a passion for AI culminated in the immense honor of the Punjab State Topper title. Besides getting access to state-of-the-art tools to fuel my future research and development endeavor, I gained world-class knowledge during the Samsung Innovation Campus (SIC) AI Program. It helped me in gaining hands-on experience and applied AI to solve real-world challenges, especially in aeronautical and technical domains,”

    During Samsung Innovation Campus (SIC) AI Program, Devesh and his team worked on innovative AI capstone project which was presented before the jury panel as part of the final assessment.

    “Our team developed the advanced AI-powered system AI Research Agent, a Retrieval-Augmented Generation (RAG) platform designed for intelligent querying of private document collections. Organizations, researchers, legal professionals, and HR teams often work with large collections of documents. Traditional search methods rely heavily on keyword matching and require significant manual effort to locate relevant information. The project was developed to address the limitations of traditional document search systems, which often struggle with contextual understanding, retrieval accuracy, learning adaptability, and response speed,” said Devesh.

     “The developed system demonstrated significant improvements over traditional document retrieval approaches with faster response generation with integration of modern AI techniques, full-stack development, database systems, and intelligent automation into a single practical solution.  By combining modern RAG architecture with innovative retrieval and reasoning mechanisms, this system provides a fast, intelligent, and user-friendly solution for knowledge discovery and resume evaluation. This project not only enhanced our technical expertise in Artificial Intelligence and Full-Stack Development but also strengthened our problem-solving, teamwork, and professional communication skills. It stands as a significant achievement of our Samsung Innovation Campus 2025 journey and reflects our commitment to building impactful AI solutions for real-world challenges,” he added.

    Congratulating Devesh Panwar for being named “Punjab State Topper” AI under the Samsung Innovation Campus Samsung Innovation Program, Deepinder Singh Sandhu, Senior Managing Director, Chandigarh University, said, “Devesh’s achievement reflects Chandigarh University’s focus on experiential learning and industry-academia collaboration.  Through the Samsung Innovation Campus AI Program, CU students gain practical exposure to AI and building solutions for real-world challenges. This accomplishment reflects not only Devesh’s commitment to excellence but also the growing culture of innovation and industry-oriented learning at Chandigarh University,”.

    “Since its inception, Chandigarh University has set benchmarks for world-class education with its dynamic hands-on experiential learning model, industry-aligned programs, dynamic fraternity, state-of-the-art infrastructure facilities and impeccable placements. Samsung Innovation Program is also part of our initiatives to develop a future-ready talent pool equipped with advanced capabilities in AI, loT, Big Data, and Coding and Programming. By bridging the gap between theoretical learning and real-world application, this collaboration helps in providing CU’s computer science and computing students exposure to cutting-edge and emerging technologies.  CU’s this partnership with Samsung is focused on building future-ready talent equipped with industry-relevant skills in AI and emerging technologies,” Sandhu said.

    He said Chandigarh University’s Institute of Computing (UIC) prepares students for a successful career in computing, to create and disseminate computing knowledge and technology. “Chandigarh University carries a vision of crafting next-gen IT professionals who can take up industry challenges effectively and our Institute of Computing (UIC) prepares students for a successful career in computing, to create and disseminate computing knowledge and technology.  UIC’s hands-on approach paves the way for a smooth transition to the workforce after graduation. Our students are equipped with the best knowledge, skills and passion to succeed in any number of computing careers.   CU’s Institute of Computing renders cutting-edge education ranging from the expertise in traditional software development -to- modern computing technologies. Fully-equipped industry-sponsored labs, industry-aligned curriculum, and accreditations and validations by top companies such as Intel, Microsoft, Google Android, Red Hat etc. give our students an exclusive edge over others,” the Chandigarh University CMD said.

    Sandhu said the latest edition of QS World University Rankings has yet again reaffirmed Chandigarh University global standing as a top educational institution. “Continuing its remarkable rise among the world’s leading higher education institutions, Chandigarh University (CU) has made impressive strides in the latest edition of prestigious QS World University Rankings 2027 by securing an overall world rank of 526, an increase of 49 ranks as compared to 575th rank in QS’ 2026 Rankings. This is for the fifth consecutive year that Chandigarh University’s global rankings have witnessed an impressive surge with CU’s world rank going up by an impressive 274 ranks — from the 800th rank in 2023 to 526th in 2027’s Rankings,”.

    “As per the latest QS World University Rankings, with All India Rank of 13 among all universities in the country as compared to 16th rank in 2026’s rankings, Chandigarh University now ranks among the top 1% of universities in India and the top 2% of universities in the World, underscoring its growing reputation as a leading institution of higher learning, both in India and globally,” he added.

    About Chandigarh University

    Chandigarh University is a NAAC A+ Grade University and QS World Ranked University. This autonomous educational institution is approved by UGC and is located near Chandigarh in the state of Punjab. It is the youngest university in India and the only private university in Punjab to be honoured with A+ Grade by NAAC (National Assessment and Accreditation Council). CU offers more than 109 UG and PG programs in the field of engineering, management, pharmacy, law, architecture, journalism, animation, hotel management, commerce, and others. It has been awarded as The University with Best Placements by WCRC.

    Website address: https://www.cuchd.in/

    Photo: https://mmx.prnewswire.com/media/MS1885145/PRESS-PIC-001-SAMSUNG-CU-STUDENT.jpg?id=OA2769782&token=eyJhbGciOiJkaXIiLCJlbmMiOiJBMjU2R0NNIn0..tz96RqadDKMvzkEj.hSUhhTBdc9ZsrJjdBxEgY3wlJi0695tAGCi_yhGtBbdiThMARSwsYuRxoaEaAC1HccJGtnxglefy4fXZDdGfD-4OdjVgfOBZDHtwSaDWfS9i0sxsJ9uscOPXaiNP1iwN6to.iJaPyZAn7rk4NN9I54uvhg

     

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    ECB Warns Stablecoins May Drain Bank Deposits—Here’s What That Means – Decrypt

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    ECB Warns Stablecoins May Drain Bank Deposits—Here’s What That Means – Decrypt



    In brief

    ECB board member Cipollone warned Friday that stablecoin growth could strip European banks of retail deposits, on top of the fees and transaction data they’re already losing to mobile payment platforms.
    Two-thirds of card payments in the euro area route through non-European schemes, and 13 of 21 eurozone countries have no national card scheme of their own.
    The ECB named 36 payment service providers for a digital euro pilot starting in the second half of 2027, days after the European Parliament voted 416 to 169 to begin formal legislative negotiations.

    European banks are losing the payments war in installments. First came mobile apps, which took their fees and transaction data, then digital payments and startups took even more control. Now the ECB is warning that stablecoins could take the thing that really hurts: their deposits.

    Piero Cipollone, an executive board member of the European Central Bank, delivered that message Friday at a banking conference in Rome, and framed the digital euro as the structural answer.

    “Even traditional debit card payments are becoming less popular. In fact, mobile payments are on the rise and they already exceed one in ten point-of-sale transactions in Ireland, the Netherlands and Finland,” he said.

    “When their customers use mobile payments, banks typically pay higher fees than those associated with debit cards and often do not receive any information about the payment, so they lose both fees and data,” Cipollone added. “If the use of stablecoins increases in the future, banks will also lose retail deposits.”

    

    He was speaking to Italian cooperative bank executives who have their own reasons to be nervous: Half of Italy’s cooperative bank branches serve towns with fewer than 10,000 people, where the loss of payment data could hollow out the local lending business.

    Stablecoins add a new layer to that problem. They’re privately issued crypto tokens pegged 1:1 to a fiat currency—almost always the dollar—that let users hold and move money entirely outside the banking system. Think of them as a digital dollar you keep in an app rather than a bank account. Even fintechs like PayPal, Stripe, and others rely on the traditional banking system one way or another.

    The global stablecoin market sits at roughly $300 billion, per DefiLlama data, and is almost entirely dollar-denominated.

    Cipollone is worried that the massification of stablecoin adoption may render cash deposits irrelevant. Mobile payments cost banks fees and data; stablecoins could cost them the deposit base they rely on to make loans.

    Deposits aren’t just a number in a ledger. They’re the raw material banks use to extend credit to businesses and homebuyers. Fewer deposits means less lending—and for small cooperative banks with thin margins and local customer bases, that’s an existential problem, not a spreadsheet one.

    The ECB’s proposed fix is, ironically, a digital euro: a government-issued, electronic form of cash distributed through—not instead of—commercial banks. Under the current design, banks keep customer accounts, earn interchange fees, and retain transaction data. The ECB has already named 36 payment providers—including Deutsche Bank, UniCredit, and Revolut—for a 12-month pilot starting in the second half of 2027.

    The obvious objection is that a risk-free, government-backed digital wallet could drain deposits just as surely as a stablecoin. The ECB has guardrails in mind: the digital euro will pay no interest, removing the incentive to park large sums in it, and holding limits will cap how much anyone can keep in a digital euro account. The bank’s own financial stability analysis concluded the design poses no material risk to bank liquidity.

    Critics haven’t been fully convinced, and the ECB’s repeated stablecoin warnings haven’t visibly slowed the market. But the legislative machinery is now moving.

    Per Cipollone, negotiations on the digital euro are already underway being approved on July 9, with the first session held four days later. Lawmakers are targeting a deal by the end of 2026. First issuance is eyed for 2029.

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    Cardano Pumps as Network Moves to Further Decentralize Development – Decrypt

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    Cardano Pumps as Network Moves to Further Decentralize Development – Decrypt


    In brief

    Input Output will transfer control of Cardano’s Haskell node, Plutus platform, Daedalus wallet, and Hydra scaling tool to outside specialist companies starting in August, with the full transition running through 2027.
    The handover comes one day before the Van Rossem hard fork activates on July 18 at 21:44 UTC, taking Cardano to Protocol Version 11 and cutting smart contract execution costs.
    ADA ticked up about 2% to roughly $0.165 on Friday, but remains nearly 95% below its 2021 all-time high.

    Cardano’s founding developer is letting go. Input Output announced Friday it will hand control of core blockchain infrastructure to outside specialist firms, beginning in August—the Haskell node, Plutus smart-contract platform, Daedalus wallet, and Hydra scaling technology are all going to external hands.

    The firms taking over include Se7en Labs, a development agency with a Solana infrastructure background, and Teragone, a cryptographic research team that already leads development of Mithril, Cardano’s stake-based signature protocol. At least three independent node implementations in Haskell, Rust, and Go will run in parallel, overseen by community bodies Intersect and Pragma. The transition runs through 2027.

    

    The new motto of the blockchain is “Built by many, owned by all.”

    Founder Charles Hoskinson called it the final push of the Voltaire era, the governance and decentralization phase Cardano has been building toward since 2024. “Our partners are ready, and the ecosystem now has many diverse options,” he said in the IOGroup announcement.

    Tomorrow—July 18 at 21:44 UTC—the Van Rossem hard fork goes live on mainnet. Ratified on July 13 with 77.63% approval from delegated community representatives, the upgrade takes Cardano to Protocol Version 11 and introduces new Plutus built-in functions designed to cut smart contract execution costs.

    Cardano, which trades as ADA, is up about 2% on the day, trading near $0.165, at $6 billion market capitalization. Open interest in ADA futures sits around $193 million, with a long-to-short ratio of 2.84, meaning most traders are still betting on a spike.

    For Input Output, the handover closes a chapter. The company will shift focus to research and new ventures through IO Labs and IO Ventures, leaving the community to prove whether a decentralized engineering model can move faster than the one it’s replacing.

    Should you buy the dip?

    Based purely on the charts, probably not on impulse. ADA hasn’t come close to matching its 2024 highs near $1.20, and the charts aren’t encouraging: The coin has been grinding lower since August 2025, with the 50-week exponential moving average below the 200-week.

    The Relative Strength Index, or RSI, is sitting at 34. RSI measures momentum on a scale from 0 to 100, where above 70 is overbought and below 30 is oversold. The ADX, or Average Directional Index, measures trend direction and it’s pointing at a strong bearish long-term trend. Buying here is a leap of faith, not a conviction trade.

    That said, ADA has surprised traders before. If Van Rossem delivers on its cost-reduction promise, Leios arrives on schedule, and decentralized engineering turns out to be more productive than the status quo, those holding at 16 cents could be looking at serious upside.

    Disclaimer

    The views and opinions expressed by the author are for informational purposes only and do not constitute financial, investment, or other advice.

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    Kimi K3 Just Triggered DeepSeek Flashbacks for the Stock Market – Decrypt

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    Kimi K3 Just Triggered DeepSeek Flashbacks for the Stock Market – Decrypt


    In brief

    Moonshot AI launched Kimi K3 on Thursday—a 2.8-trillion-parameter open-weight model that ranked alongside Claude Fable 5 and GPT 5.6 Sol.
    Semiconductor stocks cratered Friday, with the VanEck Semiconductor ETF (SMH) falling below key support for the first time since April.
    Full model weights go public by July 27. If they hold up under independent testing, the pressure on U.S. AI companies to justify their infrastructure spending gets significantly harder to dismiss.

    China did it again. Moonshot AI launched Kimi K3 in the dead of night and markets woke up today doing what they always do when a Chinese lab closes the gap: They panicked.

    Semiconductor and AI stocks dropped across the board Friday. Taiwan’s benchmark fell more than 6%. Japan closed down 4%. The Nasdaq slid 1.5%, its worst session of the week.

    The DeepSeek comparison seems well deserved. When DeepSeek dropped R1 in January 2025, the assumption that frontier AI required frontier spending—and the chip orders to match—cracked overnight. Nvidia shed around $590 billion in market cap in a single session. This time the damage spread across the sector.

    The VanEck Semiconductor ETF (SMH) fell below its EMA support band—the moving average tracking the price trend over the prior months—for the first time since April, extending a rout that has put it more than 20% below its late-June record high.

    On the Artificial Analysis Intelligence Index—an independent composite benchmark that aggregates model performance across reasoning, knowledge, mathematics, and coding—K3 scored 57, ranking above Claude Opus 4.8 and GPT-5.5, practically on par with Claude Fable 5 and OpenAI’s GPT-5.6 Sol, beating them in specific benchmarks at a fraction of the price. Full weights drop July 27 under a Modified MIT license which means small labs will have that model available for free.

    Wall Street analysts largely saw this coming. Bernstein’s Robin Zhu called the release “confirmatory”—another data point in a trend that’s been building all year. Morgan Stanley analyst Gary Yu framed K3 as the product of steady compound progress rather than a shock. “K3 has received positive feedback globally, signaling an all-round catch-up of Chinese LLMs with U.S. leaders in model size, performance, and pricing,” he wrote.

    

    Bernstein analyst Robin Zhu also framed this as a catch-up. “At a high level, K3 feels confirmatory of our views that (1) AI [state of the art] continues to evolve rapidly; and (2) China AI can continue to keep pace with global [state of the art], and take some share over time.”

    Moonshot is backed by Alibaba, which put $1 billion into the company in 2024 at a $2.5 billion valuation. The startup now sits at roughly $31.5 billion.

    As Decrypt covered in May, Moonshot already has deeper roots in U.S. developer circles than most realize—Cursor’s Composer 2 was found to be running on Kimi K2.5 without disclosure before the Cursor team acknowledged the open-source base.

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    China’s Kimi K3 Is Out—And Beats Claude Fable and GPT 5.6 Sol on Key Benchmarks – Decrypt

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    China’s Kimi K3 Is Out—And Beats Claude Fable and GPT 5.6 Sol on Key Benchmarks – Decrypt


    In brief

    Moonshot AI released Kimi K3 on July 16—a 2.8-trillion-parameter open-weight model that beats US labs on specific specialized benchmarks.
    K3 is priced identically to Claude Sonnet 5 ($3 per million input tokens, $15 per million output tokens) while scoring closer to Fable 5.
    Full model weights—the files that let anyone run, fine-tune, or build on the model locally—drop by July 27 under a modified MIT license, making K3 the largest freely available AI model in history.

    Moonshot AI just put out the biggest Chinese open-source model ever released, and it topped Claude Fable 5 at writing scripts.

    Towards AI’s Writing Elo—a benchmark where models write real scripts judged blind against published versions, scored using the same Elo system that ranks chess players—put Kimi K3 at 2,840, above Fable 5 (max) at 2,760. That’s a ranking Anthropic’s team has historically dominated.

    K3 also claimed the top spot on Arena AI’s Frontend Code Leaderboard—a ranking built from thousands of pairwise human votes on code generation tasks, again Elo-scored—with 1,679 against Fable 5’s 1,631. First place in six out of seven frontend domains.

    The Artificial Analysis Intelligence Index—a score built from nine independent evaluations covering coding, reasoning, agentic work, and knowledge, rated 0 to 100—puts K3 at 57, with Claude Fable 5 at 60, GPT-5.6 Sol at 59, and Claude Opus 4.8 at 56. That places K3 as the third-most capable model on the composite, with Fable 5 beating it just by 3%.

    If you want to have an idea of what it can do, this is a zero-shot result of a prompt asking the model to build an iOS clone. For comparison, this is the best approximation shared on social media using GPT 5.6 Sol and a much elaborate prompt.

    What this thing actually is

    K3 packs 2.8 trillion parameters—the numerical values that store a model’s knowledge—in a mixture-of-experts architecture. Mixture of experts splits those parameters into 896 “expert” subnetworks and activates only a fraction for any given task. That’s how you get frontier-level intelligence without melting the server room.

    “It is the world’s first open-source model in the 3-trillion-parameter class, designed for frontier intelligence scenarios including long-horizon coding, knowledge work, and reasoning,” Moonshot AI says. That’s not marketing theater: DeepSeek’s V4-Pro tops out at 1.6 trillion parameters, Moonshot’s own K2 at one trillion. K3 roughly doubles the nearest open-weight competitor on the size chart.

    It comes with a one-million-token context window—tokens are the basic unit of information an AI processes, about three-quarters of a word each—native image and video understanding, and always-on reasoning.

    Two architectural techniques underpin the efficiency gains. Kimi Delta Attention speeds up decoding for long sequences—up to 6.3x faster at million-token contexts. Attention Residuals routes information selectively across model layers rather than accumulating it uniformly, adding about 25% training efficiency at under 2% extra compute cost—together yielding roughly 2.5x better scaling efficiency than K2.

    Benchmarks are nice, Prices are nicer

    Kimi K3 costs $3 per million input tokens and $15 per million output tokens—the same rate as Claude Sonnet 5, Anthropic’s mid-tier model. The difference is that Sonnet 5 is Anthropic’s middle-ground offering; K3 is sitting three points below Fable 5 on the Artificial Analysis composite. Per task across that nine-benchmark suite, K3 runs $0.94 versus $1.04 for GPT-5.6 Sol and $1.80 for Opus 4.8.

    In other words, this model offers top of the line performance at mid-tier level prices.

    As Decrypt covered in May, the pricing gap between Chinese and American frontier AI ran 15–30x earlier this year. K3 doesn’t undercut at DeepSeek rates—it prices like a Western mid-range model—but delivers near-frontier performance at that level. For teams building on the API this represents a major cost improvement.

    

    If Anthropic goes ahead with its intentions of making Fable 5 available only via API, K3 becomes the nearest open-weight alternative to whatever model currently sits second in the industry—at half the per-task cost of Opus 4.8. That’s the scenario benchmark chasers are already running the math on.

    K3’s launch is the argument U.S. chip export controls advocates don’t want to have. The U.S. restricted Nvidia’s H800 GPUs from export to China in late 2023; Moonshot confirmed it trained earlier models on those chips. K3’s own benchmark documentation references H200s and what the company calls “a GPGPU from an alternative vendor”—widely interpreted as Huawei Ascend hardware—without specifying where that hardware sits.

    Moonshot AI president Yutong Zhang framed the constraint directly at Davos this year, per Silicon Republic: “We knew we didn’t have the luxury to simply scale up compute… That forced us to focus on fundamental research and efficiency.” Bank of America analysts, in a note after the launch, wrote that K3 proves “pre-training scaling, paired with architectural innovation, can still deliver step-change gains for flagship Chinese models” under those constraints.

    Moonshot is one of the so-called AI Tiger startups that have collectively shifted the global model landscape without access to the chips Washington said they’d need. Whether that’s an argument for tighter export controls or an argument that they don’t work is a policy question Washington hasn’t settled.

    The asterisk you should read

    K3’s hallucination rate on AA-Omniscience—a benchmark that measures how often a model confidently fabricates an answer it doesn’t know—jumped from 39% to 51% compared to predecessor K2.6. More correct answers overall; more made-up ones too. The model also acknowledges in its own documentation that it can be “excessively proactive,” making unexpected decisions on a user’s behalf during long autonomous tasks.

    For teams that ran the Kimi K2.6-based tooling and want to upgrade, K3 is a meaningful step up on most fronts—but that hallucination delta is worth stress-testing before you trust it with anything that needs to be accurate.

    If you want to try it for free, you can. It’s available on Kimi’s official website. But good luck: The servers are so packed that tasks get interrupted constantly due to traffic constraints, making it barely usable. A better alternative is to either pay for a subscription or use it over an API.

    Weights will be released on July 27. Those will be available for big enterprises and businesses. No domestic GPU, no matter how big, is currently able to handle a model this size.

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    Three Men Jailed for Posing as Police in $5.3M UK Crypto Fraud – Decrypt

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    Three Men Jailed for Posing as Police in .3M UK Crypto Fraud – Decrypt



    In brief

    Three men have been jailed in the UK for a £4 million cryptocurrency fraud in which they impersonated police officers to trick eight victims into handing over their holdings.
    The gang built convincing fake police websites and laundered the stolen crypto through a complex network, spending it on cars, Rolexes and luxury holidays, the Metropolitan Police said.
    Police have recovered about £1 million linked to victims and are still tracing assets.

    Three men have been jailed in the UK for a £4 million ($5.3 million) cryptocurrency fraud in which they posed as police officers to convince victims to hand over their coins—then spent the proceeds on Rolexes, designer shopping and luxury holidays.

    The trio phoned eight victims claiming to be officers, warned them their crypto was at risk, and talked them into sharing account details or moving funds to what they believed were secure police accounts, the Metropolitan Police said in a statement. The group had built convincing fake police websites, and the coins were immediately stolen and funneled through a complex laundering network.

    At Southwark Crown Court on Thursday, Anthony Ikenwe, 29, and Kevin Nwamma, 25, were each sentenced to six years for conspiracy to commit fraud and five years for money laundering, to run concurrently. Hamza Bashir, 23, was handed three years and nine months for fraud and three years for laundering, also concurrent.

    Rolexes, a Dubai cash stash and the Maldives

    Detectives found the men living far beyond their means. One had a recorded income of just £444 a year, yet the group bought a car worth almost £60,000 with crypto, kept around £500,000 in cash in a safety deposit box in Dubai, and holidayed in Thailand, Japan, Paris, Mykonos, the Maldives and the Seychelles.

    They shopped at Harrods, Hermès and Louis Vuitton and routinely converted crypto into prepaid payment cards, according to the Met. Officers linked more than £1 million in crypto to wallets controlled by Ikenwe, and traced stolen funds flowing into bank accounts tied to Nwamma’s luxury chauffeur business. Luxury goods recovered in the searches were valued at more than £26,000.

    The case began when victims came forward in January 2025. The Met’s Cryptocurrency Team said it used a data-driven approach—piecing together blockchain transactions, exchange records, communications, financial records and internet service provider data—to link what first looked like separate crimes into a single organized network operating across multiple platforms and jurisdictions.

    

    “This was a highly complex investigation into a group of calculated manipulators who exploited victims’ trust by pretending to be police officers,” said Detective Inspector Geoff Donoghue of the force’s Cryptocurrency Team, adding that, “Criminals should be under no illusion—policing is evolving alongside technology.”

    In November, officers raided seven addresses across London and Essex, arresting the three men and seizing luxury goods, cryptocurrency and 40 mobile phones. They recovered around £1 million tied to victims. Ikenwe and Nwamma pleaded guilty in April, while Bashir denied involvement and stood trial, changing his plea on the eighth day after being shown extensive evidence.

    Posing as the authorities

    Impersonating police has become a recurring thread in crypto crime. The closest parallel to the Met case came last year, when a scammer posing as UK police stole $2.8 million in Bitcoin from a victim’s hardware wallet. In the US, fraudsters posing as Denver police convinced a woman she had missed jury duty, then had her feed cash into a Bitcoin ATM to clear a bogus warrant—one of a wave of impersonation scams the FBI says has hit older Americans hardest.

    Sometimes the fake officers turn up in person. In France, robbers dressed as police held a couple at knifepoint in a $1 million Bitcoin robbery, while in Ukraine, men posing as cops were arrested for extorting $250,000 in Tether from an entrepreneur.

    The Met said it is still working with UK and international partners to identify others linked to the conspiracy and to claw back assets for the victims.

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    Leaks Reveal Suno Fed Thousands of Hours of Deezer, YouTube and Pond5 Data Into Its AI – Decrypt

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    Leaks Reveal Suno Fed Thousands of Hours of Deezer, YouTube and Pond5 Data Into Its AI – Decrypt



    In brief

    A hacker using the Shai-Hulud worm breached Suno in 2025 and leaked source code showing the platform scraped over 113,000 hours from YouTube Music, 62,000 from stock library Pond5, and 12,000 from Deezer, among other sources.
    The same intrusion reached customer emails, phone numbers, and Stripe payment data for what the hacker describes as hundreds of thousands of users.
    Suno’s own California compliance disclosure had already acknowledged that its training data may include music “subject to intellectual property protection”

    A hacker broke into AI music platform Suno and walked out with source code that documents, in precise detail, exactly where the company’s training data came from.

    The breach was first reported by 404 Media, which reviewed the leaked files. It confirms what the music industry had been saying in courts since 2024.

    The intruder claims to have used a piece of malware called the Shai-Hulud worm—named after the enormous sandworms in Frank Herbert’s Dune. Suno, one of the largest AI music generators online, lets users type a text description and receive a full song in seconds; building that capability required a substantial training dataset—a collection of audio files used to teach the model what different genres and styles sound like.

    

    The leaked material consists of scraping instructions and internal logs from 2023 and 2024, offering a rare look at how those pipelines are actually assembled.

    The dataset breakdown is specific. According to internal file comments reviewed by 404 Media, the training library included 113,879 hours of YouTube Music, 152,162 hours of tagged YouTube tracks, 62,117 hours from stock music library Pond5, 12,287 hours from Deezer, and 17,615 hours in a dataset labeled genius_hq, associated with material collected through Genius. The code also documented plans to download roughly 1 million hours of podcast audio via RSS feeds.

    One internal file tracking YouTube Music ingestion alone logged 2,013,545 music clips. That’s millions of recordings covering decades of audio—and the appetite wasn’t limited to music.

    The hacker claimed to have accessed records associated with hundreds of thousands of customers, including emails, phone numbers, and Stripe-related information. Suno disputes that sensitive personal information was compromised.

    The company says it identified the incident in November 2025 and called it “limited.” Suno determined the exposure primarily involved outdated source code no longer in use and concluded that individual customer notifications weren’t required under applicable privacy laws. Users are only finding that out now, through news coverage.

    Here’s the thing: Suno had already told anyone willing to read its own website that something like this was happening. Under California’s AB 2013 law—which requires AI companies to disclose their training practices—the company publicly acknowledged that its training data may include music “subject to intellectual property protection,” and listed the corpus at tens of millions of publicly available music audio files. What the hack adds is specificity: The legal filing was vague by design, and the leaked code is not.

    The scope of AI music training was already becoming clear before anyone breached anything. In June 2026, The Atlantic published four searchable databases documenting music used to train AI models—one containing 12 million tracks, another with 9 million, and two more with around 100,000 each. You could look up your favorite artist before a hacker handed anyone source code.

    The Recording Industry Association of America had alleged in a 2025 amendment to its original 2024 lawsuit against Suno that the company was ripping songs directly from YouTube—an accusation Suno contested under a fair use defense. The suit sought $150,000 per infringement incident. The hacked source code corroborates the RIAA’s central allegation.

    Udio, which was targeted in a parallel lawsuit filed by the same major-label coalition, settled with Warner Music in November 2025 and is now transitioning to a licensed platform. Suno’s case with Sony and UMG remains active in federal court; the company’s valuation sits at $5.4 billion with around 100 million users on the platform.

    Suno did not immediately respond to a request for comment by Decrypt.

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    Morning Minute: Base Hands Its App Over to Cobie – Decrypt

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    Morning Minute: Base Hands Its App Over to Cobie – Decrypt



    Morning Minute is a daily newsletter written by Tyler Warner. The analysis and opinions expressed are his own and do not necessarily reflect those of Decrypt. And check out our new daily news show covering all of the top stories in 5 minutes, downloadable on Apple Pod or Spotify.

    GM!

    Today’s top news:

    Crypto majors fall after early week rally; BTC at $64.2k, ETH steady at $1,885
    ETFs see more inflows with $108M for BTC and $54M for ETH
    Jesse Pollak hands Base App over to Cobie, says he was wrong about content coins
    Ostium exploited for $18M in DeFi’s latest attack
    Trump expected to meet with Senator today to talk Clarity Act ethics provisions

    🔵 Base Hands Its App to Cobie as Jesse Pollak Admits “I Was Wrong” on Social

    Jesse Pollak, the Coinbase executive who has been running the Base blockchain, handed the consumer Base app back to Coinbase and gave it to the infamous trader Cobie. Cobie joined Coinbase after it acquired his onchain fundraising platform Echo, and Pollak says he’s now focused on the Base chain itself rather than the app.

    In his announcement post, Pollak said his 2024-2025 strategy rested on two bets: that builders would drive adoption and that growth would come from onchain social. While he stands by the first, he flatly admitted the second was wrong. The social corner he championed, Farcaster, Zora, miniapps, and creator coins, has in his words “disintegrated completely,” leaving Base trailing rivals in perps, prediction markets, tokenization, and payments. He closed with a public apology: “hopefully we can shut up about content coins now. i was wrong and i’m sorry.” That apology echoes Brian Armstrong’s comments from earlier this week when he said Base “messed up” on content coins.

    Pollak now wants to build Base into “the blockchain for global finance,” arguing that the combination of crypto, stablecoins, perps, prediction markets, and tokenization can bring a billion people onchain. He set trading, payments, and agents as Base’s three priorities for 2026.

    As for Cobie, he will be responsible for trading products at Coinbase (CB app / Pro / Baseapp). And he’s got his work cut out for him. He faces competition on multiple fronts: 1) CEXs like Kraken, which are hungry for growth ahead of potential IPO, 2) memecoin apps like Pump Fun and Fomo who have hundreds of thousands of users, 3) Robinhood itself, which offers competing products and made a major splash onchain this past week, and 4) Kalshi, which is growing its prediction market into the perps space. He’s facing an uphill battle to say the least. But if anyone in crypto is capable, Cobie might be the single best bet…

    🌎 Macro Crypto and Markets

    Crypto majors are mostly red in midweek pullback; BTC -1% at $64.2k; ETH +1% at $1,885; SOL -2% at $76; HYPE -3% at $65.85
    ONDO (+16%), NIGHT (+4%) and UNI (+4%) led top movers
    Oil even at $80; Gold even at $4,035
    Stock futures are mixed; DOW +0.2%, Nasdaq -0.7%
    Stripe bid $53 billion to acquire PayPal alongside Advent, a deal that would merge Stripe’s Bridge and Tempo stablecoin rails with PayPal’s PYUSD
    Strategy’s CEO said the company feels “very secure” until Bitcoin hits $8,000-$10,000
    Trump is expected to attend a White House meeting later today to hash out the CLARITY Act’s contested ethics section
    Cantor Fitzgerald and Securitize are collaborating on blockchain-based IPOs, pushing tokenization from secondary trading into primary issuance
    South Korea will modify a 76-year-old law to classify crypto as national assets, a foundational step toward integrating it into the financial system
    Japan reclassified crypto as a financial asset, paving the way for a flat 20% capital-gains rate
    Chamath published a 73-page report on crypto privacy, evaluating the models of Monero and ZCash amongst others

    Corporate Treasuries & ETFs

    Meme Coin Tracker

    Meme leaders were mostly red; DOGE -1%, SHIB -2%, PEPE -2%, PENGU +1%, TRUMP even, BONK -5%
    Robinhood chain tokens were led by Tendies (+400%) and Index (+20%) while Cashcat fell another 20% and Pons fell 35%
    Solana leaders included HBULL (+55%) and SOLdiers (+48x); ANSEM fell 25% to $170M

    💰 Token, Airdrop & Protocol Tracker

    🚚 What is happening in NFTs?

    NFT leaders were mostly flat; Punks even at 32.4 ETH, BAYC -1% at 8.9 ETH, Pudgy +1% at 4.42 ETH; Hypurr’s +8% at 188 HYPE
    Invisible Friends (+50%) and Mocaverse (+26%) led top movers; nameless dread (+30%) and beef brothko (+44%) big movers for diewithmostlikes following his auctions

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    Meet Bonsai: The First 27B AI Model That Fits on Your Phone – Decrypt

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    Meet Bonsai: The First 27B AI Model That Fits on Your Phone – Decrypt


    In brief

    PrismML’s Bonsai 27B is a 27-billion-parameter AI model compressed to 3.9 GB—small enough to run on an iPhone 17 Pro Max at 11 tokens per second, the first time a model at that capability tier has cleared a smartphone’s memory budget.
    The ternary variant retains 94.6% of full-precision benchmark performance, outperforming conventional “2-bit” Qwen builds that are nearly twice as large and collapse on math and coding tasks below 4 bits.
    Apple is in early talks with PrismML about the underlying compression technology, per CNBC, with the company targeting a compressed Gemma model next in the pipeline.

    I models eat up a lot of memory. A 27-billion-parameter AI model, considered medium-sized by industry standards, needs roughly 54 GB of memory to run on half precision. Most laptops can’t hold that. Some desktop rigs can’t either.

    Earlier this week, PrismML released one at 3.9 GB—small enough to fit on an iPhone.

    Parameters are the number of dials and tweaks a model can handle. The more parameters, the denser and more capable a model is.

    Bonsai 27B is the first 27B-class model to clear the memory ceiling of a consumer smartphone, running at 11 tokens per second on an iPhone 17 Pro Max. (Tokens are the basic unit of information that AI models can handle and produce.) The ternary variant, at 5.9 GB, hits around 26 tokens per second on an M5 Pro laptop. Both are free under Apache 2.0.

    

    The compression method, built on Caltech intellectual property, reduces each model weight from 16 bits of floating-point precision to a single sign—+1 or -1 in the binary build, one of three values in the ternary. Each group of 128 weights shares a 16-bit scaling factor, landing the binary variant at 1.125 bits per weight: 14 times smaller than the full-precision original. The ternary model adds a zero state for slightly more expressive power and settles at 1.71 bits.

    In easier terms, this means a ternary AI model uses only three settings for each internal value—negative, zero, or positive—while a standard AI can choose from about 65,000 settings.

    PrismML did that without losing much of the output quality.

    What makes this different from conventional “low-bit” models is that nothing gets a higher-precision escape hatch: embeddings, attention, and the full language model head are all compressed end-to-end. Most quantized builds keep certain sensitive layers at full precision, which ends up increasing their size as a tradeoff for better quality. Bonsai doesn’t play that game.

    This is the second major release in the family. In March, PrismML shipped Bonsai 8B, a 1.15 GB model that proved the 1-bit architecture could survive at 8 billion parameters without its reasoning collapsing. The jump to 27 billion is where the stakes change—that scale is where sustained chain-of-thought reasoning, reliable tool use, and multi-step agentic behavior actually emerge consistently—the things smaller models still fumble.

    Benchmarks

    Across 15 benchmarks evaluated in thinking mode on NVIDIA H100 GPUs—spanning knowledge, math, coding, and tool use—Ternary Bonsai 27B averages 80.49, or 94.6% of the full-precision model. The 1-bit variant hits 76.11.

    Overall, on benchmarks, the models perform much better than Gemma 4 or Qwen 3.6 in terms of how much potential they offer for their size.

    The models are pretty good for what they offer, and considering how little resources they require, they take small hardware (smartphones and lower end PCs) to another level in terms of capabilities. AIME25 and AIME26, modeled on the American Invitational Mathematics Examination, come in 93.7% for Ternary Bonsai 27B versus 95.3% for the much bigger Qwen 3.6B. Bonsai scores 86 points in codig vs 88 for Qwen 3.6 and 77% on general knowledge vs 83 for Qwen 3.6.

    The model also uses a hybrid attention backbone where roughly 75% of the layers are linear rather than full quadratic attention. That architecture is what makes a 262K-token context window practical on-device—something a standard attention stack would make prohibitively expensive on phone hardware.

    We tested it

    We ran Bonsai 27B ourselves. Coding takes iteration: single-shot prompts won’t compete with cloud frontier models. Being local and free makes that irrelevant. For our Zombie Type game—a first-person typing-horror browser game—two vibe coding rounds produced clean collision detection, proper scoring logic, and graphics that held together. The model grasps structure early; the second pass refines rather than rebuilds.

    Interestingly enough, some models (like the skeletons) looked more elaborate than the ones from GPT 5.6 Sol. It doesn’t mean it’s better by any means, just that on this task it produced a cute skeleton whereas the AI king made a poorer stylistic choice.

    The game is available for testing here.

    Creative writing is a more qualified story, and the criteria is more subjective.

    Roughly speaking, the results aren’t particularly imaginative if you have a zero-shot prompt in mind.

    That said, Bonsai produces stories with consistent internal logic, pacing, and arc—better, or on par with Claude Haiku or even Sonnet on lower effort on comparable prompts. For a model that runs entirely on your own hardware with no API costs, that’s a lot to say.

    The story it created can be found in our Github repository.

    PrismML also ships a DSpark speculative decoding layer alongside the model—a lightweight drafter that proposes blocks of candidate tokens, which the main model verifies in a single forward pass rather than generating token-by-token. On an H100 that adds a 1.37x throughput boost with no change in output quality, since verification preserves the exact output distribution. On Apple Silicon it’s not yet enabled by default, but for GPU serving it’s a real gain.

    Apple’s interest adds a commercial dimension. PrismML CEO Babak Hassibi confirmed to CNBC that the company is in early talks with Apple, which is evaluating the compression technology for potential on-device use.

    Hassibi said a compressed Gemma model is next in the pipeline, followed by larger frontier models; 1-bit Bonsai 27B is available for free download now under Apache 2.0. If you need a primer on running models like this locally, check out our guide.

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    Sony’s stablecoin plan sends PlayStation crypto rumors racing ahead of the facts

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    Sony’s stablecoin plan sends PlayStation crypto rumors racing ahead of the facts


    According to online chatter, you’d be mistaken to think that Sony will soon let PlayStation users buy games using a Sony-issued cryptocurrency. However, the crypto community may be getting ahead of itself.

    On July 2, the Office of the Comptroller of the Currency granted preliminary conditional approval for a proposed Sony Bank-owned trust bank called Connectia Trust. Neither that decision nor Sony Bank’s announcement names PlayStation, the PlayStation Store, or game purchases.

    The approval simply outlines a financial-services structure that could support payments on Sony properties in the future, but a PlayStation product is not part of the public record.

    Infographic separating confirmed Connectia Trust proposal details from unconfirmed PlayStation payment claims.

    What Sony has proposed

    Connectia Trust would be wholly owned by Sony Bank. The OCC decision says the proposed trust would issue a dollar-backed stablecoin, maintain reserves, provide custody and support transfers in a restricted, permissioned closed-loop network.

    Its customers would include U.S. retail customers who already have relationships with Sony Group or its subsidiaries, as well as Sony Group companies.

    Circle gets permission to open a US bank but cannot take ordinary deposits or make loansCircle gets permission to open a US bank but cannot take ordinary deposits or make loans
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    Circle National Trust will open with custody for Circle and its affiliates, while custody for select institutions and USDC reserve management remain future possibilities.

    Jul 11, 2026 · Liam ‘Akiba’ Wright

    That framework could be useful for a consumer platform. It describes a payment system confined to approved Sony properties and defined customers, not an open cryptocurrency that can be spent broadly across the internet.

    Still, the filing uses general terms. It does not identify which consumer services would join the network or say that games could be bought with the token.

    Viral social media posts are making the leap many readers would make upon first seeing a Sony stablecoin plan: PlayStation is the company’s best-known consumer platform, so a Sony-controlled payment rail can seem like a route to game purchases. Reactions also focused on the prospect of a tightly controlled closed ecosystem. Obviously, mere online speculation does not make it a Sony product announcement.

    Connectia also has not cleared its main regulatory hurdle. The OCC’s action was preliminary conditional approval, and the trust cannot begin business until it meets pre-opening requirements and receives final approval. Sony Bank says it is preparing for a possible 2027 opening, subject to required approvals, and explicitly states that neither the opening date nor stablecoin issuance is guaranteed.

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    Washington has started selecting which crypto firms control custody at a national levelWashington has started selecting which crypto firms control custody at a national level
    Related Reading

    Washington has started selecting which crypto firms control custody at a national level

    A fast cluster of OCC approvals suggests the US is formalizing who controls custody, settlement, and stablecoin infrastructure.

    Apr 3, 2026 · Gino Matos

    A PlayStation feature would require another decision after that. The proposed network is limited to Sony Group and subsidiary platforms, but the filing does not commit any named product to use it.

    Sony would need to specify the product, its eligible customers, and what they could buy before a PlayStation purchase flow could exist.

    In October 2025, Sony completed a partial spin-off of its financial-services business and retained a 16.40% stake in Sony Financial Group, rather than keeping it as a consolidated subsidiary, according to Sony’s corporate record.

    That does not prevent coordination, but it makes the trust-bank approval only one element of a potential PlayStation-payment plan.

    Stablecoin regulation converts issuers into psuedo-banks while adding a barrier to entry for smaller playersStablecoin regulation converts issuers into psuedo-banks while adding a barrier to entry for smaller players
    Related Reading

    Stablecoin regulation converts issuers into psuedo-banks while adding a barrier to entry for smaller players

    Stablecoin regulation is giving issuers legal clarity, but compliance costs may leave the market to the biggest firms.

    Jun 21, 2026 · Andjela Radmilac

    Sony Bank now has a conditional route to build a U.S. stablecoin and custody operation for a restricted Sony network. It has not announced PlayStation crypto payments.



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