BTC $77,157.97 -0.28%
ETH $2,522.71 -0.56%
BNB $726.32 -0.10%
XRP $1.36 -0.06%
SOL $101.44 -1.42%
TRX $0.3399 +0.39%
DOGE $0.0847 +0.26%
ADA $0.2072 +0.20%
BCH $225.53 -1.80%
LINK $11.51 -1.05%
HYPE $79.66 -1.36%
AAVE $125.84 +0.16%
SUI $0.7226 -1.14%
XLM $0.1799 +0.46%
ZEC $1,122.40 -5.18%
AAPL $333.10 +0.14%
AMZN $256.51 -0.10%
GOOGL $341.06 +0.75%
MSFT $495.03 -0.03%
META $648.49 +0.21%
NVDA $218.33 -0.08%
TSLA $367.30 +0.63%
SNDK $1,626.40 -0.27%
INTC $102.07 -0.83%
SPCX $150.04 -0.54%
MU $967.45 -0.76%
AMD $515.99 +0.18%
BTC $77,157.97 -0.28%
ETH $2,522.71 -0.56%
BNB $726.32 -0.10%
XRP $1.36 -0.06%
SOL $101.44 -1.42%
TRX $0.3399 +0.39%
DOGE $0.0847 +0.26%
ADA $0.2072 +0.20%
BCH $225.53 -1.80%
LINK $11.51 -1.05%
HYPE $79.66 -1.36%
AAVE $125.84 +0.16%
SUI $0.7226 -1.14%
XLM $0.1799 +0.46%
ZEC $1,122.40 -5.18%
AAPL $333.10 +0.14%
AMZN $256.51 -0.10%
GOOGL $341.06 +0.75%
MSFT $495.03 -0.03%
META $648.49 +0.21%
NVDA $218.33 -0.08%
TSLA $367.30 +0.63%
SNDK $1,626.40 -0.27%
INTC $102.07 -0.83%
SPCX $150.04 -0.54%
MU $967.45 -0.76%
AMD $515.99 +0.18%

yc

All
Article
Flash

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.

first_img Google disassembles retired servers to recycle DDR4 in response to memory shortages

Google's Senior Director of Supply Chain Infrastructure, Nikhil Cherian, revealed that to overcome memory bottlenecks, Google is developing software and hardware solutions and dismantling retired servers to recycle DDR4 components to establish an internal recycling supply chain. Google has designed special hardware adapters to connect the previous generation DDR4 to the new generation of AI servers while importing retired servers to remove their DDR4 modules for recycling.Cherian stated that the AI industry has rapidly shifted from being compute-constrained to memory-constrained, with high-performance memory accounting for about 75% of the bill of materials cost for a given AI server. A Goldman Sachs report indicated that memory prices will continue to rise in the third quarter, with personal computer DRAM prices expected to increase by 18% to 23% and server DRAM prices expected to rise by 13% to 18%. Trendforce data shows that in August, the spot market prices for DDR4 8GB and DDR5 8GB rose to $142 and $133, respectively.The two TPU ASICs launched by Google this year have been optimized for memory design, claiming to reduce memory demand to one-sixth of the original. The TPU8i chip features a dedicated layered memory design that relies on a high-speed DDR5 memory architecture to perform host-level tasks, with each chip equipped with 288GB of HBM3e high-bandwidth memory.

Chairman of the Solana Foundation: Capital, assets, and ownership are entering a token super cycle

Lily Liu, the chair of the Solana Foundation, stated that funds, assets, and ownership are migrating to an all-weather internet infrastructure, forming a long-term token supercycle.Tokenization is not only about moving assets onto the chain but also about changing the assets themselves, allowing value to be issued, held, financed, and traded in a market that never closes.She believes that stablecoins have proven that funds can flow onto the chain globally, financial institutions are pushing for asset tokenization, and blockchain infrastructure is beginning to meet the demands of real economic activities for speed and cost, while AI economic agents require programmable money.With these factors converging, any value with clear ownership could be tokenized and gain broader distribution, financing, and trading channels.In the past year, the trading volume of RWA on Solana reached hundreds of billions of dollars, covering tokenized U.S. Treasury bonds, stocks, and private credit; during the same period, stablecoin transfer volume exceeded $4.7 trillion.Liu stated that tokenization can also allow more investors to break through geographic, minimum investment, and qualification restrictions, and enable the assets held to be used for collateral or to generate returns. Although the current on-chain market size is still far below that of traditional markets, the relevant infrastructure could potentially reach 5.5 billion internet users globally in the future.

Cryptoquant Founder: The peak of this Bitcoin bull market cycle may be driven by global institutional and ETF demand

Cryptoquant founder and CEO Ki Young Ju stated that the peak of the current Bitcoin bull market cycle may be driven by institutional funds and ETF demand outside the United States. He pointed out that deeper stablecoin liquidity and tokenized asset infrastructure will expand global market participation. Using South Korea as an example, Ki Young Ju mentioned that the country currently does not have a spot Bitcoin ETF, retail investors cannot purchase overseas-listed spot Bitcoin ETFs, and most companies are unable to open trading accounts to buy BTC. South Korea has phased in corporate participation, with the Financial Services Commission (FSC) roadmap covering about 3,500 listed companies and qualified professional investors, but financial institutions and other companies are still excluded.Strategy's Bitcoin bank evaluated 25 major institutions covering trading, custody, digital asset products, financing, and corporate participation, with an overall adoption rate of 32%. RWA.xyz data shows that the global tokenized asset distributed asset value is $38.63 billion, an increase of 2.65% compared to 30 days ago. The Bank for International Settlements (BIS) stated that stablecoins have the potential to enable faster, programmable payments, but current designs may pose risks to financial integrity, liquidity, and currency. Ki Young Ju pointed out that the cumulative net inflow before the launch of the U.S. spot Bitcoin ETF was about $57 billion over two years, and the next phase will be global institutionalization, with more institutions adopting BTC as a strategic asset, and countries lacking ETFs will also improve related investment channels.

Zhao Changpeng: It is difficult to predict the outbreak point of the next cycle, and we do not rule out large AI companies issuing tokens

Zhao Changpeng stated at the "Bitcoin Asia 2026" conference in Hong Kong that both the RWA and AI sectors are currently very strong. Stablecoins, centralized exchanges, decentralized exchanges, and Meme tokens, which have been growing, will continue to grow, and NFTs may return in some form. It is difficult to predict what the next breakout point will be, just as it was impossible to predict the coin issuance craze at the beginning of 2017 and the NFT craze six months before it exploded; these all require entrepreneurs to create.He also mentioned that the funds used by billions of AI agents for automated buying, selling, negotiating, and trading in the future will definitely be cryptocurrencies, likely starting with stablecoins, and then gradually integrating other public chain assets like Bitcoin. He has discussed the possibility of issuing tokens with several top AI companies, as building data centers requires huge amounts of capital, with the cost of 1 GW of computing power being about $30 billion to $50 billion. Some AI companies plan to build hundreds of GW of computing power in the coming years, so they are considering issuing data center tokens that would allow holders to gain rights to use computing power in the future. Additionally, the payment scenarios for AI agents may be implemented later than trading scenarios; currently, AI companies are more focused on helping agents find optimal trading solutions, while trading scenarios require AI to process information quickly, which can increase trading efficiency by about ten times.
app_icon
ChainCatcher Building the Web3 world with innovations.