Daily Edition · Page 1

THE DAILY INDEX

Technology, AI, software, security, crypto and business

Across today’s newsletters

Today’s Index

DEEPSEEK GETS SILICON VALLEY TALKING

Many in the tech industry have been praising DeepSeek over the recent release of its reasoning model, R1. R1 seemingly matches or beats OpenAI's o1 model on certain benchmarks. It only cost $5.6 million to train, much less than the hundreds of millions of dollars it has taken leading US companies to train their models. The company achieved all this while facing US sanctions that prohibit the sale of advanced chips to Chinese companies. DeepSeek's AI assistant is now the top free app in the Apple App Store.

ORACLE AND MICROSOFT ARE REPORTEDLY IN TALKS TO TAKE OVER TIKTOK

Oracle, Microsoft, and a group of investors are in talks to take over TikTok's global operations. The deal will allow ByteDance to keep a minority stake in TikTok while the app's algorithm, data collection, and software updates will be overseen by Oracle. Oracle's server network already provides the bulk of TikTok's backbone. President Trump earlier issued an executive order giving TikTok and others a 75-day reprieve from any enforcement action related to the US' requirement that ByteDance divest from TikTok.

WHAT DID DEEPSEEK FIGURE OUT ABOUT REASONING WITH DEEPSEEK-R1?

Chinese AI lab DeepSeek recently released a reasoning model trained on a GPU cluster a fraction the size of any of the big western AI labs that is better than the current best reasoning models. Reasoning models are able to 'think' about questions, which results in better answers. DeepSeek used a reinforcement learning approach, as opposed to a fine-tuning approach, to train its reasoning model, which resulted in cost and quality benefits. This approach can only really train the model on coding and mathematics, but this might not matter as superintelligence in coding/mathematics might transfer to other domains - this has yet to be demonstrated in practice.

WHAT HAPPENS WHEN WE CAN'T JUST BUILD BIGGER AI DATACENTERS ANYMORE?

AI's continued growth may ultimately hinge on a new kind of supercomputer that spans entire countries. This will involve stitching together existing datacenters to distribute the workload. The infrastructure required to stitch datacenters together already exists, but it is tuned more for disaster recovery and high-availability than large-scale AI training. Research is already underway to improve the technology, which will help address power challenges by allowing datacenters in different regions to work as one.

INTRODUCING SCOPEDB: MANAGE DATA IN PETABYTES FOR AN OBSERVABILITY PLATFORM

ScopeDB is a database built on top of S3 that unleashes the power of cloud elasticity and workload isolation. It achieves ten times cost-efficiency and performance improvement compared to databases built with shared-nothing architecture. ScopeDB servers use a single stateless binary, so there is no need to manage local disks, data sharding, or complex leader action. A demo playground to test out the features of ScopeDB is available.

TLDR IndexPage 1