Bitget integrates Robinhood Chain into its onchain trading functionality.

New York Fed President Williams said today that U.S. inflation remains significantly above the Federal Reserve’s 2% target, and the central bank still has “a lot of work to do” to curb inflation amid high energy prices and strong demand driven by AI investment. He called another interest rate hike this year a “reasonable” expectation, but stressed that future policy decisions will depend on economic data. Williams noted that the U.S. economy has shown resilience after major shocks, but persistent energy price pressures and strong demand from AI investment have raised inflation risks. He pointed out that U.S. inflation has exceeded the Fed’s target for five consecutive years. The Federal Reserve unanimously raised interest rates by 25 basis points last week, lifting the federal funds rate target range to 3.75%-4%. The latest dot plot shows 16 of 18 officials expect at least one more rate hike before the end of 2026. Williams said each future policy meeting will be decided based on the latest economic and inflation data. Markets have also increased bets on an October rate hike: CME FedWatch data shows that as of September 24, the market’s probability of a Fed rate hike in October is around 70%, up from about 54% the previous day. In addition, Williams noted that AI investment has become a new variable on the demand side. While AI investment could drive productivity growth in the coming years, its actual contribution to overall productivity remains limited for now.

The European Banking Authority (EBA), in its response to the European Commission’s targeted consultation on the Markets in Crypto-Assets (MiCA) framework, is calling for crypto lending to be incorporated into the EU’s MiCA regulatory regime. This includes cases where crypto asset service providers facilitate client access to decentralized finance (DeFi) lending protocols. The EBA recommends the European Commission conduct a cost-benefit analysis of legislative changes, add intermediated crypto lending to MiCA’s list of regulated services, and potentially impose specific compliance requirements and oversight measures. It also proposes relevant rules for crypto firms that offer clients access to DeFi lending protocols. Potential measures outlined by the EBA include suitability tests for users, leverage limits, enhanced disclosure requirements, possible restrictions on lending access involving MiCA-authorized asset reference tokens or e-money tokens, and a certification system for DeFi lending protocols. The EBA notes that crypto lending continues to grow across the EU; prior research shows lending activities exist in at least 16 member states. Easier access to DeFi via crypto firms and AI tools is increasingly blurring the line between centralized and decentralized finance.

Binance announced in an official statement that it will gradually add Hyperliquid (HYPE) to its services including Simple Earn, Buy Crypto, Convert, VIP Loan, and Margin starting September 24. HYPE’s flexible product will launch on Simple Earn at 19:00 UTC+8 on September 24, with subscriptions opening immediately. Within one hour of HYPE’s spot trading going live, users can purchase HYPE via payment methods such as bank cards, Google Pay, and Apple Pay, and trade HYPE with assets like BTC and USDT on Binance Convert with zero fees. Additionally, HYPE will become an eligible borrow asset for VIP Loan within one hour of its spot listing. Binance’s margin trading will add HYPE as a borrow asset at 19:00 UTC+8 on September 24, and launch HYPE/USDT and HYPE/USDC cross-margin and isolated margin trading pairs; portfolio margin will also support HYPE and the above-mentioned trading pairs simultaneously. Binance reminded that newly listed tokens usually have high volatility, so users should pay attention to risk management.

Beating AI Express News: Apple has open-sourced LensVLM-9B, a vision-language model purpose-built for processing long documents, trained on Qwen3.5-9B-Base. When handling long documents, the model first compresses the entire document into low-resolution pages for a quick scan to locate relevant pages, then reads the original text or high-definition images on those pages—eliminating the need to load the full document into the model’s context window. Per the paper’s tests: For a 100-page document, reading the full text directly requires 51,273 tokens, while LensVLM uses just 8,090 tokens. The corresponding KV cache drops from approximately 1.6GB to 253MB, an 84.2% reduction, with no significant accuracy loss after compression. Among 7 document question-and-answer tasks, direct full-text reading yields an average accuracy of 72.4%, while LensVLM hits 68.9% at roughly 4.3x compression. Compared to the approach of converting text to images for model recognition (at around 5x compression), LensVLM lifts accuracy from 31.3% to 68.9%. That said, the model is currently slower: After locating the relevant page, LensVLM must call an additional tool to read the original text, requiring two consecutive inference runs. The paper notes each answer takes approximately 17 seconds; without the compression scheme, directly inputting the full document as text into Qwen3.5-9B takes about 8 seconds to generate a response.

Insight Beating AI Flash News: Personal AI assistants have been popping up en masse lately, and some in Silicon Valley are already poking fun at these products. Tech video creator Max Musgrave has developed a fake product called Sidehoe, billed as "the first AI assistant to help you manage your dating pool". It reads iMessage chats, remembers the names, birthdays, and preferences of each date, alerts you to who you’ve been ghosting for 9 days, checks for conflicting appointments, misnamed messages, and whether the same flirty line has been sent to multiple people. Sidehoe has copied nearly all standard features of personal AI assistants: it stores information, proactively reminds users, drafts responses, and claims all data is processed locally. To avoid being detected by partners, notifications are disguised as delivery alerts, and the app is hidden behind a seemingly functional calculator. It even offers a $9.99/month Pro plan, plus a "Monogamy" plan for managing only one person, which notes "No app required". Only at the bottom of the page does it admit that Sidehoe is a parody, not an actual product. Musgrave runs Strive Haus, a San Francisco-based creative studio that specializes in producing product launch videos and brand content for tech companies. Familiar with these launch routines, Sidehoe’s product demo, feature naming, and subscription page are all highly realistic.

Flash News from Dongcha Beating AI: Today, a personal AI assistant founded by Qi Junyuan—founder of Teambition and former head of Doubao PC—has officially launched in China. Today was previously in open beta overseas, and this marks its first time offering downloads and registrations to Chinese users. The basic version is permanently free; new users receive 100 million Tokens and a 1-month Pro subscription. It currently supports Mac, Windows, Linux, iOS, and Android. Today continuously accesses users’ authorized emails, calendars, notes, and documents, and retains key contacts, preferences, commitments, and pending tasks. When tasks have new updates, it proactively reminds users and leverages cloud computing to handle operations on web pages, files, and other applications. In a prior test by PingWest, users asked Today to schedule an interview. It first located contacts via Gmail, checked the calendar, recommended a time, drafted an email, and sent it directly after user confirmation. The next day, after the recipient replied, the journalist issued no further instructions—Today independently picked up the new email and the previous interview task, and continued to provide next steps. Accessing emails, checking calendars, and sending messages on behalf of users are not new capabilities. What differentiates Today is its ability to keep tasks in the system after a conversation ends, and follow up when triggers like email replies, schedule changes, or other conditions arise. However, this also poses challenges: the more it remembers and the more proactive it is, the higher the requirements for memory accuracy, permission control, and privacy protection.