Miguel Alonso Jr.

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Practitioner with public evidence across Agents & robotics.

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past 30d
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past 30d
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Building generally intelligent agents - ML, RL, Robotics

Articles & links

Miguel Alonso Jr. reposted
Alexia Jolicoeur-Martineau @alexiajm.bsky.social

Simple beats complicated: We show that switching to a sliding-window attention mask with attention sinks (at no cost) beats linear attention post-training. Huge thanks to my collaborators Rhea Sukthanker, ‪Pashmina Cameron‬, and Emy Gervais. Paper: arxiv.org/abs/2608.28444

Sliding-window beats linear attention arxiv.org
AI Weekly's analysis
  • On the long-context reasoning tasks the paper cites (Needle-in-a-Haystack and BABILong), SWA scored 2 to 10 times higher than post-trained linear attention.
  • The authors argue linear-attention retrofits have not been properly compared to simpler baselines, and that SWA with sinks needs no post-training at all.
  • Their bottom-line recommendation is to switch to SWA rather than continue post-training linear models for inference memory savings.
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Miguel Alonso Jr. reposted
Tim Kellogg @timkellogg.me

if you're having trouble with Astra, it's probably old skills. Point your agent at these two URLs and use them to upgrade skills: 1. developers.openai.com/blog/rethink... 2. github.com/openai/codex...

Rethinking skills and prompts for GPT-6 Astra | OpenAI Developers developers.openai.com
AI Weekly's analysis
  • OpenAI is telling developers to strip back the Skills descriptions and AGENTS.md instructions they carried over from GPT-5.6 Sol when moving to Astra.
  • The post says Astra runs tests on its own without being told to, so the old 'make sure to run the tests' instructions have become redundant noise.
  • Astra can stop earlier than Sol did and hand work back for review, so developers are told to define what 'done' looks like up front.
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Miguel Alonso Jr. reposted
Lynn Cherny @arnicas.bsky.social

Google DeepMind article on 15 tears of Ai game research

Exploring new frontiers of AI and games research — Google DeepMind deepmind.google
AI Weekly's analysis
  • Google DeepMind announced a research partnership with Fenris Creations, the studio behind EVE Online, to probe frontier AI capabilities inside the 20-plus-year-old space MMO.
  • The four capabilities in scope are named plainly: continual learning, memory, long-horizon planning, and complex multi-agent dynamics.
  • SIMA 2, powered by Gemini, now operates as an interactive companion across No Man's Sky, Valheim and Hydroneer, with an Aura Guidance system inside EVE.
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Miguel Alonso Jr. reposted
Tim Kellogg @timkellogg.me

I made a skill for Claude Code/Codex/etc. for selecting models based on Artificial Analysis reported benchmarks & costs I figure it'll be useful for letting models setup subagents well, based on the actual task at hand github.com/tkellogg/mod...

GitHub - tkellogg/model-selection: A skill for model selection github.com
AI Weekly's analysis
  • The skill queries Artificial Analysis' API so subagents can rank available models by benchmark scores and cost before picking one for a task.
  • API calls are cached on a daily basis to stay under Artificial Analysis' free tier limit of 100 requests per day.
  • Install is a git clone into ~/.claude/skills, with an optional symlink into ~/.codex/skills for people running two agents.
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Miguel Alonso Jr. reposted
Sung Kim @sungkim.bsky.social

GLM-5.3 is now open-weight. Their most capable model for agentic coding and cyber defense is now available to download, run, and customize. Weights: huggingface.co/zai-org/GLM-5.3 Tech blog: z.ai/blog/glm-5.3

z.ai
AI Weekly's analysis
  • GLM-5.3 launched on August 14, 2026, keeping GLM-5.2's base and lifting Terminal-Bench 3.0 from 4.6 to 28.3 through post-training alone.
  • On CyberGym vulnerability discovery, GLM-5.3 scored 84.5%, slightly ahead of Claude Mythos 5 at 83.8% and GPT-5.6 Sol at 83.6%.
  • Z.ai says the model surfaced 2,436 vulnerabilities across 269 open-source projects, 1,097 rated critical or high, and delayed weights about two weeks.
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Miguel Alonso Jr. reposted
@unsloth.ai

Kimi K3 can now be run locally! ✨ The 1-bit model retains ~78.9% accuracy after we shrunk it from 1.56TB to 594GB (-62% size). Run on a Mac Studio + 128GB RAM device. Kimi K3 is the strongest open model to date. Guide: unsloth.ai/docs/models/... GGUF: huggingface.co/unsloth/Ki…

unsloth/Kimi-K3-GGUF · Hugging Face huggingface.co View on Bluesky →

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