DeepSeek is rushing to get its next-gen R2 model out sooner than expected (2 minute read)
DeepSeek is looking to maintain the momentum gained by the debut of its R1 reasoning model by rushing its new R2 model to market as quickly as possible. It first planned to launch R2 in early May, but it now wants to move the release date forward. The model will likely have improved coding skills and be able to reason in languages other than English. DeepSeek has a chance to shake up the market once again, especially with GPT-4.5's arrival in a few weeks.
|
Anthropic's Claude AI is playing Pokémon on Twitch — slowly (3 minute read)
Claude Plays Pokémon is a livestream on Twitch where Anthropic's newest AI model, Claude 3.7 Sonnet, plays a game of Pokémon Red. Anthropic says Pokémon is a good benchmark for its model as it can effectively 'think' through the sorts of puzzles the game contains. The model has managed to win three gym leader badges. However, it has run into several issues, such as being unable to navigate around a wall and confusing other NPCs for Professor Oak inside his laboratory.
|
|
Science & Futuristic Technology
|
Is it Lunacy to Put a Data Center on the Moon? (4 minute read)
One of the payloads on SpaceX's Falcon 9 rocket launch today is an Intuitive Machines mission that will stay on the surface of the moon for approximately three weeks before returning to Earth. The lander contains a mini data center belonging to Lonestar Data Holdings that weighs just 1 kilogram and contains 8 terabytes of SSD storage. Moon-based data centers would be protected from Earthly hazards such as natural disasters, war, and other disruptions. They would also not be subject to the laws of any nation, allowing them to accommodate a diverse customer base. These data centers could be powered entirely through solar and naturally cooled through the environment.
|
|
Programming, Design & Data Science
|
Get coding help from Gemini Code Assist — now for free (4 minute read)
Gemini Code Assist for individuals is a free version of Gemini Code Assist that is now globally available in Visual Studio Code, GitHub, and JetBrains' IDEs. Powered by Gemini 2.0, it supports all programming languages in the public domain. Google is offering up to 180,000 free code completions per month on Gemini Code Assist. The tool supports up to 128,000 input tokens in chat, allowing developers to use large files and ground Gemini Code Assist with a broader understanding of their codebases.
|
Fast columnar JSON decoding with arrow-rs (25 minute read)
A lot of data pipelines spend the bulk of their CPU time deserializing JSON. If you want to build a fast stream processing engine, you need to start with a fast JSON deserialization strategy. This post is aimed at helping developers gain some intuition for how to work with columnar data, something many engineers find challenging and unfamiliar with in our typically row-oriented world. It covers batched decoding, column building, streaming extensions, and more.
|
|
AI Promise and Chip Precariousness (32 minute read)
There is currently sufficient incentive for the leading research labs to raise money and continue investing in new foundation models, even as competition drives API prices down relentlessly. Getting to a future where the US has a strong AI industry running on US-made chips will take significant interventions in the market to undo the overwhelming incentives for US companies to simply rely on TSMC. Such a shift will take time, which is why making Taiwan indispensable to China's technology industry is the price that needs to be paid in the meantime.
|
The Deep Research problem (6 minute read)
While the examples of the work Deep Research can do OpenAI has provided look great, there are several issues with the tool. It appears the tool made intern-level mistakes when sourcing its data for one of the examples. While these models are definitely getting better, any model that generates mistakes can't be trusted. The best use cases for tools like this so far are for tasks where the error rate doesn't matter.
|
|
GoatDB (GitHub Repo)
GoatDB is a real-time, version-controlled database for Deno, React, and low-friction deployments ideal for prototyping, self-hosting, single-tenant apps, and ultra-light multi-tenant setups without heavy backends or complex DBs.
|
|
|
Love TLDR? Tell your friends and get rewards!
|
|
Share your referral link below with friends to get free TLDR swag!
|
|
|
|
|
Track your referrals here.
|
|
Want to advertise in TLDR? 📰
If your company is interested in reaching an audience of tech executives, decision-makers and engineers, you may want to advertise with us.
Want to work at TLDR? 💼
Apply here or send a friend's resume to jobs@tldr.tech and get $1k if we hire them!
If you have any comments or feedback, just respond to this email!
Thanks for reading,
Dan Ni & Stephen Flanders
|
|
|
|
