Image created with OpenAI GPT-Image-1. Image prompt: rich crimson, bright ivory, deep navy Independence-Day palette, vibrant, celebratory, wholesome, authentic, photorealistic Statue of Liberty harbor at dusk with sparklers on ferry deck scene featuring a digital scoreboard showing benchmark bar charts; natural lighting, subtle film grain, high detail
if you block AI from accessing your content, there will be no one left to read it. to elaborate: the future of search is lightweight research agents. a lot of businesses are already seeing significant traffic come from ChatGPT. if you block AI scrapers, i will never read your content because o4-mini-high will send me to your competitor’s website”” / X https://x.com/vikhyatk/status/1940227029389255109
Many firms built around the limitations & cost assumptions of GPT-3.5 class models, and are now stuck with complex solutions that are more expensive & worse than a reasoner without any scaffolding You need to build solutions with an eye towards riding the cost/performance curve.”” / X https://x.com/emollick/status/1939494862438453717
Huawei announces open-sourcing of Pangu models to accelerate AI application, value creation https://www.ecns.cn/news/sci-tech/2025-07-01/detail-ihesxvny3991876.shtml
To supercharge its AI push without triggering a government review that would come with acquiring other companies, Meta bought a 49 percent non-voting stake in data-labeling firm Scale AI for $14.3 billion and hired its founder and CEO, Alexandr Wang, and key staff. Wang will”” / X https://x.com/DeepLearningAI/status/1940153434671362268
Tencent released Hunyuan-A13B, a new open-source hybrid reasoning model It nears or matches models like o1 and DeepSeek R1 on major benchmarks, while remaining efficient enough to run on a single GPU Also includes “”fast and slow”” modes to adjust efficiency levels https://x.com/rowancheung/status/1939601169271197973
The real star of the show is the (Baidu) 21B A3B, ~30% smaller than Qwen3 30B A3B and better on most benchmarks! 🔥 https://x.com/reach_vb/status/1939584854045466791
Earlier this month, we launched the Image Edit Arena. Today, the Image Edit Leaderboard 🏆 goes LIVE, powered by more models and all your community votes. 🏆 In 1st place: GPT-Image-1 by @OpenAI 💠 2nd-4th: Flux 1 Kontext Max, Pro & Dev by @bfl_ml 💠 5th: Gemini 2.0 Flash https://x.com/lmarena_ai/status/1940795298449924220
Code agents underperform because public SWE corpora are small, poorly verified, and cover few repositories. Skywork‑SWE builds a rigorously tested dataset of 10,169 Python bug‑fix tasks and fine‑tunes a 32B code agent. Performance climbs with data, reaching 38% pass\@1 and 47% https://x.com/rohanpaul_ai/status/1939616650002878712
RT @omarsar0: Evaluating LLM-based Agents This report has a comprehensive list of methods for evaluating AI Agents. Don’t ignore evals.…”” / X https://x.com/omarsar0/status/1940009835342246277
What happens if you put a full scientific paper into AI and ask it to find known errors in proofs, tables, etc? Every model before o3 fails completely, o3 gets 21% (its better at proofs, worse at tables & figures). Progress & perhaps a second opinion, not yet autonomous science. https://x.com/emollick/status/1940064995439779962
RT @Michael_D_Moor: 🚨Preprint alert!🚨 Did you know there is a new reasoning benchmark where leading models like o3 still fall flat? (i.e.…”” / X https://x.com/_akhaliq/status/1940066518307381616
🚀 Excited to share that MiniMax-M1 is now live on the Text Arena leaderboard at #12! And has climbed to #1 in math! 🎉 As the open-source hybrid MoE model with the world’s longest context window, we’re pushing boundaries in long-context reasoning and agentic tool use.💪”” / X https://x.com/MiniMax__AI/status/1940243199500677218
Interestingly Claude-4 Opus and o3 are on the same level on METR when selecting 80% (instead of 50%) probability of succeeding on a task https://x.com/scaling01/status/1940093773440008512
Claude 4 Opus and Claude 4 Sonnet fall behind o3 on METR”” / X https://x.com/scaling01/status/1940089136104579515
LLMs still miss subtle engineering tweaks humans exploit for major speed gains. 🚀 The Automated LLM Speedrunning Benchmark shows that today’s frontier models still miss many record‑setting NanoGPT tweaks, so automated reproducibility of AI research is far from solved. 🔍 https://x.com/rohanpaul_ai/status/1940288577700503584
New IIT-JEE rankings just dropped https://x.com/bilawalsidhu/status/1939901363162349629
Test-based certification is the only way forward in food, eager to see more over time. Food is not simple anymore – it is a complex, industrial product with global supply and processing chains. Contamination can be introduced in many stages along the way from farming to harvest,”” / X https://x.com/karpathy/status/1940181840201228384
Love this project: nanoGPT -> recursive self-improvement benchmark. Good old nanoGPT keeps on giving and surprising 🙂 – First I wrote it as a small little repo to teach people the basics of training GPTs. – Then it became a target and baseline for my port to direct C/CUDA”” / X https://x.com/karpathy/status/1939709449956126910
The study asks if models like GPT‑4o truly understand images. It finds they juggle many jobs yet still trail task‑focused vision tools. Past tests could not match chat models with pixel specialists fairly. The authors turn every benchmark into quick yes‑no image checks any API https://x.com/rohanpaul_ai/status/1941086082679951554
MAI-DxO in action, tackling one of those complex cases: https://x.com/mustafasuleyman/status/1939670348330619278
AllenAI just introduced SciArena in which o3 is crushing all other models”” / X https://x.com/scaling01/status/1940065085776666679
SciArena: A New Platform for Evaluating Foundation Models in Scientific Literature Tasks | Ai2 https://allenai.org/blog/sciarena
Many of the academic papers shared on X are benchmarking papers, which are made so that current AIs will fail often (or it isn’t a benchmark for future progress) You should pay attention to the realism of the benchmark, relative rankings, and the prompts & tools given to the AI.”” / X https://x.com/emollick/status/1940100137335902627
LLMs can synthesize many programs, but how should we search among them? New from @SakanaAILabs – AB-MCTS frames code generation as an adaptive tree search, guided by external feedback. Beats baselines on synthesis benchmarks including ARC-AGI.”” / X https://x.com/ndea/status/1940166177424384354
METR results for DeepSeek V3 and R1 kinda sucks, huh? https://x.com/scaling01/status/1939770925781487779
