BREAKING: GLM-5.2 is now 1st on Design Arena.
With an Elo of 1360, GLM-5.2 has jumped ahead of the now unavailable Claude Fable 5.
And it's open weights.
This is an improvement of 4 positions and 27 Elo points to achieve one of the highest Elo scores in our code categories since Design Arena started.
Huge congratulations to the @Zai_org on the release!
🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced!
🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite.
🔷 Reasoning efficiency: Less overthinking, with 30% lower reasoning-token usage compared to K2.6.
🔷 Long-horizon coding: Improved instruction following, higher end-to-end coding task success rates.
⚡️ 6x High-Speed Mode coming soon!
🔌 Available today via Kimi API and Kimi Code.
🔗 Kimi Code: https://t.co/uvoSJKyGCY
🔗 API: https://t.co/EOZkbOwCN4
The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees.
The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance.
Access to all other Claude models is not affected.
We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible.
Read our full statement: https://t.co/bwn0sximKZ
I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem.
As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)!
I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work.
It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results?
88ms => 1.5ms
150K allocs => ~500 allocs
Incredible right? Nope.
My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path.
This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput.
The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity.
Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.
Claude Code has a new wild feature... dynamic workflow.
How to try:
set /model to opus 4.8
set /effort to "ultracode" 😂
use “workflow” in your prompt
Claude will write an orchestration script, spawn subagents swarm, verify results, and report back.
🚀 What's new on Danelfin
🌍 Now in 7 languages: 🇺🇸 🇪🇸 🇩🇪 🇫🇷 🇮🇹 🇧🇷 🇵🇱
📈 IPO analysis pages: SpaceX, OpenAI, Anthropic, Stripe and more
📋 Personal notes on every portfolio holding
👉 https://t.co/KlpEqUySwn
all these capabilities have been there for a while if you have seen the anthropic skills repo. everything that can be manipulated with code. they are productizing it even if its sloppy at first (then improving at incredible pace). all these micro announcements (even smaller updates but daily) are a way to create marketing and algorithmic momentum giving the perception of moving even faster than they are actually moving
One example attack:
1. A Comet user sees a Reddit thread where one comment has hidden instructions.
2. The user asks Comet to summarize the thread.
3. Comet follows the malicious instructions to find the user's Perplexity login details and send them to the attacker.
🚀 Danelfin ranks #9 on @Siftedeu’s 2025 Leaderboard of the fastest-growing startups in France & Southern Europe!
Honored to be among the top 10 scaleups driving innovation and growth.
📊Full ranking → https://t.co/0UcrQWeI0w
#Sifted100#Growth#Fintech#AI
NEW post: https://t.co/68x2WS3x9E
<deep breathing...> <prepares for Haterade> People are gonna be angry about this one. Especially those of y'all who've been trying to make AIO, AEO, LLMO, GEO, or EIEIO take off.
See you in the comments 😅😬
Live speech translation in Google Meet is here. Speak naturally—your words are translated in near real time while preserving your tone, voice, and expression. Available in English and Spanish, with more languages coming soon. → https://t.co/c3Do5qhPNu
#GoogleIO
AI Mode is rolling out to everyone in the US. It’s a total reimagining of Search with more advanced reasoning so you can ask longer, complex queries.
AI Overviews are now used by 1.5B people a month, in 200+ countries and territories.
And Gemini 2.5 is coming to both this week.