BTC $80,449.14 +2.10%
ETH $2,517.29 +0.90%
BNB $714.17 +1.46%
XRP $1.45 +3.22%
SOL $109.48 +8.44%
TRX $0.3377 +0.65%
DOGE $0.0891 +2.67%
ADA $0.2145 +1.54%
BCH $269.99 +0.81%
LINK $11.97 +3.79%
HYPE $84.22 +3.28%
AAVE $129.78 +3.12%
SUI $0.7834 +3.28%
XLM $0.1870 +1.57%
ZEC $813.78 +0.92%
BTC $80,449.14 +2.10%
ETH $2,517.29 +0.90%
BNB $714.17 +1.46%
XRP $1.45 +3.22%
SOL $109.48 +8.44%
TRX $0.3377 +0.65%
DOGE $0.0891 +2.67%
ADA $0.2145 +1.54%
BCH $269.99 +0.81%
LINK $11.97 +3.79%
HYPE $84.22 +3.28%
AAVE $129.78 +3.12%
SUI $0.7834 +3.28%
XLM $0.1870 +1.57%
ZEC $813.78 +0.92%

challenge

All
Article
Flash

first_img The Ethereum Foundation launches the better.codes challenge to advance the provable security of hash SNARKs

The open automated research challenge better.codes, created by the Ethereum Foundation's formal verification team in collaboration with Yukon and zkSecurity, is now live. This platform formalizes the self-contained problems from the Proximity Prize in Lean and places the machine-checked reliability bounds of koalaIRS12 on a public leaderboard, allowing anyone to contribute to improvements, advancing hash-based SNARK and post-quantum Ethereum-related security benchmarks.Solvers can bring their own AI agents to prove higher lower bounds of reliability for this Reed-Solomon proximity problem, moving towards a fixed target of 128 bits. The Lean kernel verifies each submission, and the promoted proofs will enhance the public bounds, with new lemmas, proof techniques, and impossibility results being synchronized upstream for reuse by all participants. Most hash SNARKs in production environments rely on related proximity gaps and related conclusion agreements, while the currently provable results remain below the benchmarks trusted by researchers; this challenge aims to narrow this gap in an open, incremental, and verifiable manner.koalaIRS12 originates from related papers and is end-to-end formalized in ArkLib. Participants can log in via GitHub and clone the challenge repository, submitting under fixed theorem statements and verification frameworks; results confirmed by the comparator and Lean kernel are recorded in a public repository, noting the solver and the model used. Today's launch features the reliability challenge that raises the proven lower bound of koalaIRS12 to 128 bits, with more problems potentially added later, subject to project terms.

hot_img Intel's EMIB-T advanced packaging faces yield challenges, with the first mass production target in 2027 only at 50%

According to Taiwanese media reports, Intel's next-generation advanced packaging technology EMIB-T is facing severe yield challenges. ABF substrate supplier Unimicron stated during its earnings call on July 29 that the technology is "not yet mature," and the yield target for three EMIB-T substrate suppliers (Unimicron, Ibiden, and Shinkawa) during the initial mass production phase at the end of 2027 is only 50%.EMIB-T is Intel's advanced packaging solution that competes with TSMC's CoWoS-L, differing in that it embeds the silicon bridge directly into the substrate rather than using a silicon interposer, making substrate suppliers a key factor in determining success or failure. Google's ninth-generation TPU has confirmed that it will adopt EMIB-T packaging when it goes into mass production in 2028, with MediaTek responsible for chip co-design. If the chip successfully goes into mass production, its shipment volume is expected to challenge NVIDIA. Unimicron stated that the customer (Intel) has provided a profit guarantee mechanism, ensuring that suppliers can remain profitable even if yields are poor, and that profit margins will exceed the company's average level after achieving the 50% yield target. Currently, there is still considerable uncertainty about whether EMIB-T can achieve its mass production target by the end of 2027.

U.S. employment unexpectedly shrank in July, posing a policy challenge for the Federal Reserve, as market expectations for interest rate hikes quickly declined

In July, the United States unexpectedly lost 23,000 jobs, far below the expected increase of 80,000. The increase in June was also revised down to only 20,000. Despite the weak job market, the unemployment rate unexpectedly fell from 4.2% to 4.1%. "Fed mouthpiece" Nick Timiraos commented that in July, the U.S. unemployment rate dropped to 4.09% because both the number of job seekers and the number counted as unemployed decreased; this data brought the unemployment rate to its lowest level in two years.Analysts pointed out that this disappointing report has reignited concerns about the labor market and may complicate the Federal Reserve's interest rate decisions, as policymakers need to seek a balance between weak employment and persistent inflation. As a result, market expectations for interest rate hikes quickly receded.Affected by this, U.S. stock index futures surged rapidly, with Nasdaq futures up 0.79% for the day, S&P 500 futures up 0.39%, and Dow futures up 0.27%. U.S. Treasury prices soared, with the yield on the 10-year U.S. Treasury currently down 4.29 basis points, reported at 4.627%; non-U.S. currencies generally rose, with the dollar against the yen briefly falling 80 points, reported at 157.72.At the same time, the U.S. Dollar Index DXY briefly fell nearly 30 points, reported at 99.67. Spot gold briefly rose about $40, reported at $4,351.43 per ounce.

hot_img Bloomberg: The AI investment boom intensifies the differentiation in the venture capital market, with small and medium-sized funds facing survival challenges

According to Bloomberg, the current venture capital market is experiencing significant structural differentiation. As funds concentrate on top artificial intelligence startups, many small and medium-sized venture capital funds are facing severe challenges such as fundraising difficulties, declining performance, and narrowing exit channels.The report points out that the excessive hype around artificial intelligence has distorted the venture capital market. Data shows that just five companies—OpenAI, Anthropic, xAI, Waymo, and Nscale—accounted for 78% of all venture capital transaction volume in the first quarter of this year. A large amount of capital has flowed to a few top investors who made early bets on AI, such as Founders Fund and Andreessen Horowitz, while small emerging fund managers find it difficult to compete with these leading institutions.This differentiation is directly reflected in fundraising data. Last year, newly established management companies (managing three or fewer funds) raised only about $62 billion, a significant drop of about 60% compared to the pandemic peak of $163.4 billion in 2022. Even experienced management teams raised only $84 billion last year, which is just one-third of the amount in 2022. Many LPs are facing liquidity pressures and are more inclined to demand returns on existing investments rather than commit new funds.
app_icon
ChainCatcher Building the Web3 world with innovations.