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Whoever sings down Anthropic may be disappointed

Whoever sings down Anthropic may be disappointed

Author: Alan Walker, Silicon Valley Original title: Is Anthropic's Growth Slowing Down? Source of controversy. Claude Code ARR tracking chart produced by TickerTrends. The latest data is $15.12 billion for the week of August 10, 2026, accounting for 21.9% of Anthropic's total ARR. Please note: This is an estimate from a third party agency and is not an official disclosure of Anthropic. The first section below explains how important this difference is. Alan Walker from Silicon Valley made an appointment for dinner in Hong Kong. After some hard work, he discovered that this picture had been retweeted more than 30 times, and the matching statement was similar — “Anthropic's growth has leveled off; 2 trillion dollars is a bubble.” Alan saved the image, zoomed it in, and looked at it again. The problem isn't in this picture. This picture is very well done, and the data is probably done seriously. The problem is that almost everyone who retweeted it was using it to answer a question it couldn't answer at all. 01 Let's first figure out who made this picture, there is a Claude icon in the upper left corner. The color scheme is Claude's familiar orange. At first glance, it looks like an official product. It's not. The author of this picture is TickerTrends and has his name written in the upper right corner. It is a third-party data tracking agency that uses various external signals (application data, payment panels, recruitment, channel caliber, etc.) to estimate the revenue of an unlisted company. The line in the picture is written very honestly: “tracked allocation” -- the percentage of allocations that have been tracked. Let's be clear: Anthropic has never publicly disclosed Claude Code's individual ARR numbers, not once. Every point on this curve has been estimated by an outsider. For example, this is like someone using “long queues at the entrance of a restaurant every day” to estimate its turnover and then draw a beautiful weekly curve. The length of the team does correlate with turnover, but in the middle there is turnover rate, customer unit price, takeout ratio, private room business — you see that the team is three short weeks, and the kitchen is probably being renovated in those three weeks. What is more important is the caliber itself. ARR's algorithm is “revenue for the most recent period times 12.” Enterprise software contracts are not executed evenly every day; they are signed batch by batch. Big orders signed at the end of a quarter will jump a week's curve by a large margin; if the next quarter's big orders aren't signed, the curve will go sideways. Weekly ARR tracking is extremely insensitive to this kind of blocky landing—it will paint the “pace of signing” as a “change in demand.” In a nutshell, what you have in your hand is an unofficial weekly map estimated by an outsider, with a very blunt caliber. Judging by the weight of the “bubble” under it is tantamount to using body temperature to measure blood pressure. 02 I hit myself in the face on this picture. I haven't seen anyone mention it, but it's the most interesting part of the whole thing. The picture shows two numbers: Claude Code is $15.12 billion, or 21.9% of Anthropic's total ARR. By dividing: calculate 15.12 billion ÷ 21.9% = about $69 billion. This is Anthropic's total ARR for the week ending August 10, implied by this image. The official caliber figures reported by Bloomberg, Reuters, and CNBC on August 17 were — $65 billion at the end of July. Clear: This chart, which is being used to prove “slowing growth,” its own implied total number of companies is 4 billion US dollars higher than the official figure ten days ago. Further 10 days until today, if the trend continues, more than 70 billion is a reasonable estimate (this sentence is an inference, not data). In one sentence, people who retweeted only read the number 151.2 and the height of the column, skipping the 21.9% next to it. And that 21.9% said: This company went a step further when everyone shouted “it's slowing down.” I only believe in the two numbers on the same picture that is beneficial to my opinion; this is not called analysis. 03 You are looking at the picture below. The money in the picture above has the upper and lower two pieces. Above is the absolute amount (how many billion dollars), and below is the percentage change (how much more than a percent increase from four weeks ago). The vast majority of people's reasoning is: below...

1d agoWendy#Anthropic #ARR #IPOs #MiniMax
Yao Shunyu reorganizes Tencent's multi-modal route: closer to Liang Wenfeng and away from Li Feifei

Yao Shunyu reorganizes Tencent's multi-modal route: closer to Liang Wenfeng and away from Li Feifei

Text | Miao Zheng Editor | Wang Jing Source | Letter AI Tencent's mixed element multi-modal team has undergone another personnel change. According to media reports, Lin Xudong, who was responsible for xAI's multi-modal understanding, has left xAI and joined Tencent's mixed element as the head of the multi-modal content generation algorithm. The reason this personnel news is worth paying attention to is that it takes place in the context of continuous adjustments of mixed and multi-modal teams. Over the past period of time, news of the departure of the person in charge, the transfer of researchers, and the addition of new members came out one after another within the mixed yuan. Hu Han, the former head of multimodal understanding, left his career to start a business, and Tian Yonglong and others joined Tencent. The reporting relationship between the original multi-modal team also changed with the integration of the big language model department and the multimodal model department. However, does this mean that Tencent's multi-modal team is “changing the dynasty” is currently unable to draw a direct conclusion. What can be confirmed by public information is that mixed forces have indeed experienced personnel movements and organizational restructuring. The rumor of Lin Xudong's addition is more like a new signal in this adjustment: Tencent is recombining the two routes of multimodal understanding and content generation. So the question is, what exactly did Lin Xudong come from, and what abilities can he add to Tencent? And is Tencent's multi-modal approach shifting from “generating content” to Yao Shunyu's more biased “understanding context and acting in the world”? What is Lin Xudong's origin and what can he do after joining Tencent? According to public information, Lin Xudong graduated from Tsinghua University in 2018 and then went to Columbia University to study for his doctorate. While studying at the blog, his research interests included embedded learning, video analysis, and generative models. He also participated in the Vx2Text project in collaboration with Columbia University and Facebook AI. V indicates video, x indicates unknown, can be sound, voice, or even ambient sound. 2 represents TO, and Text represents subtitles. Its logic is to first convert different modes such as video and sound into vectors similar to “language tokens”, then uniformly feed the language model for fusion, and finally generate open text by an autoregressive decoder. Transformer can only understand tokens, so AI essentially doesn't understand video and audio file formats, making it even less likely to convert them into text. For example, if a dog jumps into the water next to a swimming pool, Vx2Text's video recognizer (V) will output keywords: dog, jump, pool; sound reader (x) will output: sound of water, fluttering. Although the product function of Vx2Text is “generation,” the core difficulty of the product is “understanding.” Of course, Vx2Text doesn't simply “translate” a screen into a few sentences. Models need to recognize people, objects, movements, and events from videos, understand how these things change over time, and finally organize visual information into language. After graduating from his PhD, Lin Xudong joined DeepMind and participated in Gemini-related multi-modal pre-training and post-training work. In 2025, he also joined xAI. According to public information, it is responsible for the direction of multimodal understanding and participating in the training of multimodal content understanding and generation models. Now that he has joined Tencent Hybrid, he will be responsible for the hybrid multi-modal content generation algorithm. Lin Xudong was added not so much to improve the performance of mixed-element multi-modal generation, but rather to solve a problem that plagues all multimodals — understanding. The previous generation model was more like a picture maker. Give it a hint, and it can generate an image or a video. But as long as users make more complex requests, the model just can't keep up. For example, the characters change in the long video, the shape of the object is not consistent before and after, the camera movement does not match the spatial relationship, etc. It's not because the model doesn't generate, but because it doesn't remember and understand the world steadily. Therefore, putting Lin Xudong in the position of multi-modal content generation is probably because he “translated” multi-modality into something AI can understand. Lin Xudong's addition can only be clearly seen in a larger context. That is, now Tencent's mixed element is reorganizing its multi-modal route. In January 2025, Tencent Outstanding Scientist (Tencent Distinguished Scientist) Hu Han succeeded Liu Wei, who had previously left his job, and was fully responsible for the research and development of mixed-element multi-modal models, and also served as Tencent's mixed-element big model Tech Lead. Tencent's internal organization was adjusted in the second half of 2025. He transferred from the Multimodal Model Department to the “Frontier” Frontier Technology Research Group under the Big Language Model Department. The title was changed to Head of the Multimodal Understanding Direction, and the reporting line was also changed to report to Yao Shunyu. The actual position changed from “the head of an independent department” to a “big language model...

2d ago字母AI#AI #Li Feifei #Liang Wenfeng #Tencent

Google turns sign language into an input method: Pixel 11 can type while facing the camera

Comparative news, according to monitoring, Google DeepMind released the SL2T sign language to text model and connected it to Pixel 11's Gboard and Live Transcribe. The first support for American Sign Language to English is supported. Users can search, write messages, type in documents, and even ask Gemini questions directly by typing in sign language on their phones. SL2T uses over 100,000 hours of data training, covering more than 50 sign languages, about a quarter of which is American Sign Language. The phone will first extract the posture coordinates of the hands, face, and body, and only send the coordinates to the server for translation; the original video will not be uploaded.

8d ago

Robinhood Chain ecosystem meme coin HMM rose 167%, surpassing $20 million in market capitalization

Comparative news, according to GMGN monitoring, Robinhood Chain's ecological meme coin HMM (Thinking Cat) continued to rise, with a market capitalization of about US$20.68 million, a record high; tentatively reported at around US$19.11 million, a 24-hour increase of about 167%, with a turnover of about US$2.3 million during the same period. According to reports, the meme coin mainly revolves around the Wirebot launch/demonstration meme superimposed on the PONS header ecological narrative. Wirebot previously used Thinking Cat (HMM) as a public demonstration to obtain Robinhood Chain's early native meme label when it launched the direct coin issuance and transaction function through X posts; recently, the rise may have been driven by the rise in popularity of PONS and Robinhood Chain and the launch of alpha on a trading platform. Note: Meme coin transactions are highly volatile, mostly dependent on market sentiment and conceptual hype, and have no real value or use cases. Investors should be aware of risks.

10d ago

Tencent Hybrid Officially Releases Next-Generation Speech Recognition Model Hy ASR 3.0 Preview

Comparing news, Tencent Mixture officially released the Hy ASR 3.0 preview of the next-generation speech recognition model. Based on the language comprehension capabilities of Hy3, the latest generation big language model, the model can give accurate, consistent, and closer to the user's intention in more complex real input. Currently, this model has been launched on Tencent Cloud's official website to provide API services, and can be widely used in scenarios such as intelligent customer service, content understanding, and voice search. Yuanbao has completed its initial launch and is free to use; products such as WorkBuddy are also being added one after another.

18d ago

Uniswap launches Earn earnings feature to support self-hosted USDC, USDT, and ETH borrowing to generate interest

In comparison, Uniswap announced that the earnings product Earn has launched the Uniswap web app and wallet, and users can deposit USDC, USDT, and ETH to earn revenue without leaving Uniswap. The product launch supports the Ethereum main network, and related funds will be allocated to the on-chain lending market, and interest paid by borrowers will continue to be converted into user income. Earn uses a self-escrow model. Users only need to sign once to complete the deposit. The funds are controlled by the user from deposit to withdrawal. There is no lock-up period or cooling-off period, and they can withdraw at any time. Its underlying treasury infrastructure is provided by Morpho and managed by Gauntlet. Users can go to the supported assets page in the Uniswap web app or wallet, or find Earn through the Explore page, select the deposit amount and confirm it. If you don't have assets backed by a treasury, you can first exchange them or buy them in fiat currency. Uniswap does not charge an Earn usage fee, but users are still required to pay standard network fees.

21d ago

Google DeepMind releases Lyria 3.5 music generation model, which supports generating full songs of up to 3 minutes

Comparatively, Google DeepMind released Lyria 3.5, a next-generation music generation model, which focuses on improving the music structure, quality of lyrics, command compliance, vocal performance, and the ability to control song length. It can directly generate a complete song of up to 3 minutes, rather than just tens of seconds of audio. According to reports, Lyria 3.5 still uses a latent diffusion architecture to diffuse and generate in the temporal audio latent space. The training data is audio with text annotations of different granularity, and post-training is performed through SFT and reinforcement learning combined with human and critical feedback. SynthID watermarks are embedded in all generated content. However, Google did not disclose the scale, source, and quantified Benchmark of the training data, which only indicated a significant improvement in audio clarity and compliance with lyric instructions compared to Lyria 2. In addition, Lyria 3.5 was first integrated into Flow Music, which supports interactive music creation, stem splitting, remix, music publishing, playlist generation, and can also link Veo to generate music videos. It also supports the development of audio plug-ins, music games, and custom DAWs to further integrate Lyria, Veo, and Gemini to build a complete ecosystem covering music creation, editing, publishing, and distribution.

23d ago

MoonPay launches PayBox, an AI payment tool that supports direct payment through ChatGPT and Claude

In comparison, MoonPay launched PayBox, an AI payment tool. Users can connect it to ChatGPT or Claude to allow the AI assistant to directly prepare payment transactions such as booking air tickets, restaurants, or online shopping. Users can choose that each transaction requires a passkey approval, or that AI can complete the transaction independently after setting a limit. PayBox integrates cryptographic wallets and payment cards, supports cross-chain transactions based on x402 smart payment standards, and initially supports Solana and EVM compatible chains. MoonPay said that the wallet's private key is protected through multi-party computing (MPC) and trusted execution environment (TEE), and no single party can independently obtain a complete private key or sign a transaction, and will expand support for more AI platforms and DeFi features in the coming month.

23d ago

Update: SpaceX has joined the open source open letter signing, Anthropic is still absent

Comparative news, according to monitoring, Nvidia, Microsoft, Meta and other companies jointly issued an open letter “Open Weights and American AI Leadership” to continue expanding. The number of signatories has increased from the initial 25 to 77. Among them, SpaceX received the most attention. Musk previously only retweeted Hwang In-hoon's post on X, saying he fully supports it; Jensen was right. The company didn't sign up at the time, and now SpaceX is officially on the list. The letter asks the US government not to prematurely restrict open weight models that can be downloaded and self-deployed, and to treat normal distillation differently from illegal extraction. Anthropic still hasn't signed.

26d ago