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first_img Analysis: 91% of the YC 2026 Summer Batch are AI companies, with the application layer's proportion dropping to 39%

User chris__lu posted that they compiled all 236 companies and 470 founders from the YC Summer 2026 batch, categorizing each company into an AI technology stack layer and comparing it to the Spring batch using the same criteria. This batch still has 91% related to AI. The model companies increased from 8% to 20%, the application layer decreased from 55% to 39%, horizontal applications dropped from 58 to 32, and vertical applications remained at 25%.In the Spring, 45% of companies delivered autonomous agents, while in the Summer, it was 33%, with "agent" in a one-sentence introduction dropping from 27% to 19%. 21 companies are engaged in computational infrastructure, 11 focus on inference costs, and there are also companies for training data and reinforcement learning environments. Scale AI is listed as an alternative target by 8 companies. The industrial category increased from 12% to 24%, with 45 companies delivering physical products, 24 being robots or physical AI, and 21 companies operating their own businesses rather than selling software.This batch is the youngest, with 37% of founders being students or graduates in the last two years, 59 teams are entirely student teams, the dropout rate increased from 3% to 9%, and repeat founders decreased from 32% to 23%, with 84% having a technical background. 39 from Berkeley, 32 from MIT, and 25 from Stanford. Amazon is the largest source of talent. Sales and marketing AI decreased from 18 to 6. Only 19 founders come from AI labs, accounting for 4%. 8 founding teams come from the same previous employer.
19 minutes ago

first_img Samsung develops NVIDIA's custom NVHBM to advance 8-layer high-speed HBM4E

According to reports from Seoul Economic Daily, Samsung Electronics is developing HBM4E (seventh generation) 8-layer products that meet NVIDIA's requirements, aiming to secure its position as a core partner in the supply of customized high-bandwidth memory NVHBM. This product reduces the stacking height compared to the originally planned 12-layer and 16-layer designs. The speed specifications proposed by NVIDIA are 17-18Gbps, which is about 20% higher than the speed of Samsung's initial HBM4E samples (14.4Gbps), and will be used for NVIDIA's publicly disclosed NVLink optimized specifications for NVHBM.The use of 8 layers, contrary to the previous logic of increasing capacity by adding more stacking layers in HBM, can reduce the difficulty of post-processing and yield pressure, which is beneficial for expanding supply and is seen as NVIDIA's strategy to alleviate memory shortages. NVHBM is expected to be applied starting with the next-generation AI GPU "Rubin Ultra," which is set to launch next year. This GPU will expand the interconnection scale between GPUs from a maximum of 72 to 576, enhancing overall computing power through hundreds of GPUs equipped with faster HBM.In the customized HBM market, Samsung is more competitive compared to SK Hynix and Micron, as NVHBM requires DRAM and the production capabilities of logic chip-based bare die designs, which Samsung can integrate. Industry insiders say that Samsung has verified the highest speed levels in HBM4, which can provide an advantage in speed competition.

first_img Viewpoint: The AI application layer should not be priced based on tokens, but should be anchored to "recognizable work value."

a16z partner Sarah Wang recently published an article pointing out that AI application layer products should not price based on tokens like the model layer, but rather on "recognizable work units." The article argues that token pricing anchors the value of application products to a unit whose cost is continuously declining, making it difficult for customers to predict context length, retrieval volume, or reasoning time, and improperly compares applications to raw computing power.The article suggests a tiered pricing model based on value levels: model layer priced by tokens; application layer priced by recognizable work units for customers (such as account research briefs, code modifications, completed queries), which can be encapsulated through Credits; and scenarios that are attributable and have clear value priced directly by results (such as resolved customer service conversations, qualified leads). The design of Credits should map to different levels of work difficulty to protect gross margins and distinguish "work value" from "delivery cost." The article uses Clay as an example, where its new pricing separates Data Credits (third-party data) from Actions (orchestrated work), only passing on costs for reasoning models with significant cost fluctuations without markup. The author believes that pricing anchored to value rather than computing cost allows customers to understand spending in relation to value, while also benefiting product providers in maintaining profit margins.

first_img RockawayX acquires cryptocurrency hedge fund Relayer Capital to expand its business in the United States

Cryptocurrency investment firm RockawayX announced the acquisition of the crypto hedge fund Relayer Capital to incorporate long-short strategies into its existing platform and expand its business footprint in the United States. RockawayX manages approximately $2 billion in assets, and Relayer will be renamed RockawayX Liquid Opportunities Fund, focusing on uncovering "undervalued liquidity tokens and crypto-related stocks." After the acquisition is completed, Relayer founder Austin Barack will serve as the chief investment officer of the fund, with Forbes citing informed sources that the company plans to raise $150 million for the fund.According to the announcement, Relayer's liquidity strategy has achieved approximately 70% net returns this year, outperforming a weighted basket of Bitcoin, Ethereum, and Solana by 86% as of August 21. The strategy expresses fundamental views on crypto tokens through long and short positions and pairs trading, while reducing overall market exposure at appropriate times. RockawayX CEO Viktor Fischer stated that now is the "right time" to implement this strategy, as there are crypto companies with real revenue and strong fundamentals emerging in the market, but inefficiencies and mispricing still exist, providing good opportunities for active investors.This transaction occurs amid a recent rebound in the crypto market, with Bitcoin recording its largest weekly dollar gain in history last week, dropping 1.68% to $79,064 in the past 24 hours after briefly reaching a high of around $81,000.
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