Linera Launches Babbage Testnet

According to a report by Seoul Economic Daily, Samsung Electronics is developing an 8-layer HBM4E product as required by NVIDIA, for use in NVIDIA’s custom high-bandwidth memory NVHBM. This design cuts the number of stacked layers compared to Samsung’s original plans for 12-layer and 16-layer products. NVIDIA has set a target speed of 17 to 18 Gbps, roughly 20% higher than the 14.4 Gbps of Samsung’s early HBM4E samples. The 8-layer design reduces the difficulty of wafer thinning, precision stacking, and backend packaging, eases yield pressure, and boosts supply capacity. NVHBM is expected to debut in NVIDIA’s Rubin Ultra AI GPU, scheduled for launch next year. Rubin Ultra will expand its GPU interconnect scale from the current 72 units to up to 576 units, using more high-speed GPUs working in tandem to offset the drop in storage capacity per individual GPU. Samsung has the capability to design and manufacture DRAM, logic chips, and base dies, allowing it to offer one-stop services for custom HBM. Industry insiders point out that Samsung has already demonstrated high transmission speeds on HBM4, and as NVIDIA shifts its competitive focus from high stacking to high-speed transmission, Samsung’s related capabilities may draw more attention.

Beating AI News: Tencent has released the Hy4 preview, a new Mixture of Experts (MoE) architecture model with 770 billion total parameters, 49 billion activated parameters per inference, and a context window expanded to 1 million tokens. Compared to Hy3’s 295B total parameters, 21B activated parameters, and 256K context window, this generation’s scale has more than tripled, while the context window is roughly four times larger. This time, Tencent did not solely emphasize general benchmark scores, but specifically enhanced the model’s performance on real-world tasks including coding, office work, gaming, and scientific research. For example, the model can build a Three.js 3D website from scratch, create playable game demos in Unity, and process up to 72 financial documents at once to check for duplicate reimbursements, over-limit expenses, and budget anomalies. Hy4 was also trained and iterated alongside Tencent products such as WorkBuddy and CodeBuddy. A standout feature is that Hy4 has begun participating in its own R&D: Tencent says the model helps optimize training methods, data strategies, evaluation systems, and underlying operators, proposing its own plans, running experiments, and adjusting based on results. The code, logs, and feedback from these experiments are fed into the next R&D cycle, forming an initial self-improvement loop. The Hy4 preview is now integrated with WorkBuddy, CodeBuddy, Yuanbao, ima, Tencent Cloud TokenHub, and OpenRouter. Tencent previously teased in its financial reports that Hy4 would be larger than Hy3, and noted real product feedback as a key source for model training.

Beating AI Express News reports that Cognition, the company behind AI coding agent Devin, has reached an annualized revenue of approximately $900 million. Calculated at its current monthly revenue of around $75 million, this represents a more than threefold increase from the start of this year. The firm is also in a new round of financing, with a potential valuation of roughly $45 billion, and its growth pace is accelerating. In May this year, when Cognition secured its previous financing, it disclosed an annualized revenue of just $492 million and a $26 billion valuation. In only three months, its annualized revenue has climbed by about 83%. However, Cognition is burning cash heavily. The Information states that the company is projected to consume roughly $800 million in cash this year, with $200 million of that burned in the second quarter alone. A major portion of this spending goes toward computing power: Cognition leases a large fleet of NVIDIA servers, used both to operate Devin and train its own models, with the server setup costing hundreds of millions of dollars annually. Currently, Cognition’s enterprise business has a gross profit margin of nearly 50%. Excluding spending on training its in-house models, the company is nearly cash flow neutral. Management forecasts that annualized revenue will exceed $1.5 billion by the end of this year, and reach $4 billion to $5 billion next year.

According to Lookonchain monitoring, Bitcoin treasury firm Metaplanet transferred another 1,350 BTC to Coinbase Prime an hour ago, worth approximately $108 million. Earlier, the company bought 43,000 BTC at an average price of $96,191, totaling around $3.48 billion.

According to views from Morgan Stanley, JPMorgan Chase, UBS, Barclays, and Goldman Sachs, markets are focusing on three key aspects of Federal Reserve Chair Powell’s first speech at the Jackson Hole symposium. The primary suspense is whether Powell is a clear hawk or a neutral-to-hawk, and what inflation level would trigger his support for interest rate hikes; the market still has no clarity on his policy reaction function. The second focus is whether Powell will adjust the Fed’s policy framework, including its inflation framework, balance sheet, forward guidance, the impact of AI on productivity, and the quality of economic data. Morgan Stanley argues that these long-term issues may be more important than whether to raise rates by 25 basis points in September. The third focus is how Powell will address potential policy conflicts between the Federal Reserve and the U.S. Treasury. The U.S. Treasury is expanding long-term U.S. debt repurchases to lower long-term financing costs; if the Fed maintains high interest rates to curb inflation, it could keep long-term yields elevated. This speech may serve as an opportunity for Powell to outline how the two sides can coordinate. (Jinshi)

Crypto analyst Ali Charts has posted that Bitcoin’s current price action is forming a fractal structure similar to that of the 2022 bottom phase. In 2023, after breaking through its long-term downtrend, Bitcoin first tested the prior year’s August high, then pulled back to around $20,000 before resuming its upward trajectory. Drawing on this historical structure as an analogy, the corresponding key level to watch now is near Bitcoin’s May 2026 high, roughly $83,000. If Bitcoin faces resistance in this zone and pulls back, it could present the next major buying opportunity. However, this judgment is based on historical fractals and does not mean the trend will necessarily repeat.