Today at Google I/O, we introduced Gemini 3.5 Flash! It has become an integral part of our daily research cycle and works with all the tools we have at Google.
We used a team of agents in Antigravity 2.0 to recreate the original AlphaZero research paper and build a playable version. They coded the reinforcement learning pipeline in JAX/Flax, trained a ResNet model from scratch via self-play on multi-TPU pods, and shipped a full-stack web app so you can play against it, from just 2 prompts. .
Here’s what else makes 3.5 Flash special 🧵
This works really well btw, at the end of your query ask your LLM to "structure your response as HTML", then view the generated file in your browser. I've also had some success asking the LLM to present its output as slideshows, etc.
More generally, imo audio is the human-preferred input to AIs but vision (images/animations/video) is the preferred output from them. Around a ~third of our brains are a massively parallel processor dedicated to vision, it is the 10-lane superhighway of information into brain. As AI improves, I think we'll see a progression that takes advantage:
1) raw text (hard/effortful to read)
2) markdown (bold, italic, headings, tables, a bit easier on the eyes) <-- current default
3) HTML (still procedural with underlying code, but a lot more flexibility on the graphics, layout, even interactivity) <-- early but forming new good default
...4,5,6,...
n) interactive neural videos/simulations
Imo the extrapolation (though the technology doesn't exist just yet) ends in some kind of interactive videos generated directly by a diffusion neural net. Many open questions as to how exact/procedural "Software 1.0" artifacts (e.g. interactive simulations) may be woven together with neural artifacts (diffusion grids), but generally something in the direction of the recently viral x.com/zan2434/status…
There are also improvements necessary and pending at the input. Audio nor text nor video alone are not enough, e.g. I feel a need to point/gesture to things on the screen, similar to all the things you would do with a person physically next to you and your computer screen.
TLDR The input/output mind meld between humans and AIs is ongoing and there is a lot of work to do and significant progress to be made, way before jumping all the way into neuralink-esque BCIs and all that. For what's worth exploring at the current stage, hot tip try ask for HTML.
South Korea 🇰🇷 is now the clear #3 nation in AI — powered by the Korean National Sovereign AI Initiative there are now multiple Korean AI labs with near frontier intelligence.
A key driver of this momentum is the Korean National Sovereign AI Initiative, a government-backed, nationwide competition that incentivizes domestic model development through a multi-stage elimination process. The initiative shortlists national champions, with winners receiving direct government funding and guaranteed access to large-scale GPU capacity.
➤ In August 2025, five organizations were selected: Naver, SK Telecom, LG Group, Upstage, and NC AI
➤ In the most recent round announced last week, the field narrowed to three: LG, SK Telecom, and Upstage.
➤ A fourth finalist is expected to be selected in the coming months as the evaluation process continues
Generally, top Korean AI models tend to be open weights, and vary in size ranging from Motif‘s 12.7B Thinking model to LG’s 236B K-EXAONE. Other models, such as Korea Telecom (KT)’s Mi:dm K 2.5 Pro, are proprietary and developed with a focus on business integration with existing KT clients.
Overview of major releases:
➤ LG | K-EXAONE - The current leader in the Korean AI race and a shortlisted model in the Korean National Sovereign AI Initiative. K-EXAONE is a 236B open weights model and scores 32 on the Artificial Analysis Intelligence Index. K-EXAONE performs strongly across various intelligence evaluations from scientific reasoning, instruction following, to agentic coding. However, this model has high verbosity, using 100 million tokens to run the Artificial Analysis evaluation suite
➤ Upstage | Solar Open - Another shortlisted model in the Korean National Sovereign AI Initiative. Solar Open is a 100B open-weights model and scores 21 on the Artificial Analysis Intelligence Index. Solar Open performs well in instruction following and has lower hallucination rate compared to peer Korean models
➤ Naver | HyperCLOVA X SEED Think - A 32B open weights reasoning model that scores 24 on the Artificial Analysis Intelligence Index. HyperCLOVA X SEED Think demonstrates strong performance on agentic tool-use workflows and scores highly in the Global MMLU Lite multilingual index for Korean, highlighting its potential usefulness in a primarily Korean language environment
➤ Korea Telecom | Mi:dm K 2.5 Pro - A proprietary reasoning model that scores 23 on the Artificial Analysis Intelligence Index. Mi:dm K 2.5 Pro sees strong performance in agentic tool-use. Mi:dm K 2.5 Pro currently has no publicly available endpoint. Instead, Korea Telecom primarily intends to package this model into product offerings and use this model to serve KT’s clients
➤ Motif | Motif-2-12.7B - A small open weights model that scores 24 on the Artificial Analysis Intelligence Index. Motif-2-12.7B performs well in long-context reasoning and knowledge, but is highly token intensive - using 120 million tokens to run the Artificial Analysis evaluation suite
See Artificial Analysis for further details of the Korean models: artificialanalysis.ai
Join our Discord community to discuss more: discord.gg/92EMmeRH
아마존 원격 근무하는 직원 키 타이핑 지연이 0.1초로 평균 30ms보다 많이 느려서 조사해봤더니 북한 요원이었다고. 🤯 전수조사해서 47명의 의심되는 직원 중 44명은 와이파이 불량이었고 3명은 추가 조사중이라고. 원기사는 블룸버그인데 페이월이 있어 다른 인용 기사.
esecurityplanet.com/threats/amazon…
My CISO called me at 3 AM last Tuesday.
"We caught someone."
I asked, "Caught them doing what?"
He said, "Typing."
Let me explain.
We have an employee in IT. Great worker. Always online. Never complained. Perfect Slack etiquette.
One problem.
His keystrokes were arriving
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