mlllm.ioAI news and builder lab
AI channel Telegram Threads GitHub

Independent AI news for builders

AI news, clear context, and the projects behind the work.

Short briefs, source trails, and deeper explainers from a visible publishing pipeline — not a generic technology news feed.

2026-07-20
Google works on Frozen v2 AI chip for Gemini: Report

Google embeds Gemini architecture into silicon

Google is developing a specialized Frozen v2 chip that integrates the Gemini architecture directly into the hardware to increase energy efficiency. The shift from general-purpose accelerators to a "frozen" architecture (model-in-silicon) could radically reduce data center capital expenditures and solve the computing power shortage.

Stories tracked903Short briefs with source trails and paired longform links when available.
Explainers897Expanded pages that carry the durable context behind selected stories.
Media assets654Verified images, video posters, and source media attached to story records.
Languages planned8EN/RU first; other locales stay gated until translation quality is ready.

Start with the feed, then go deeper.

Use the news feed for quick updates, explainers for context, the blog for working notes, and projects to inspect the systems behind the publication.

/news/

Short news feed

English index for translated briefs. The current live source feed is visible under /ru/news/.

/articles/

Explainers

Selected stories rewritten as clean longform articles with context, source trail, and related links.

/topics/

Topic pages

Evergreen answers about the publishing system, quality gates, and story model without duplicating daily news.

/blog/

Builder notes

Personal thinking about agents, editorial infrastructure, product design, and open-source work.

/projects/

Project index

TG-NEWS, Task-Plan v2 Dashboard, MCP experiments, and other systems with status and repositories.

How a story moves from source to site.

  1. IngestPublic sources, research posts, company updates, repositories, and Telegram-native signals.
  2. MapDomain, vendor, importance, duplicate groups, source trail, and short trend signal.
  3. VerifyCheck facts, source links, repeated context, weak claims, and publication quality before release.
  4. LocalizePrepare English and Russian editions with language-specific headlines, terms, and links.
  5. PublishStatic HTML pages, RSS, sitemap, news sitemap, llms.txt, and cross-language links.

Latest English AI stories

English story index

Source-backed English briefs selected from TG-NEWS.
Teaser image demonstrating novel view synthesis

MetaView: High-Precision Novel View Synthesis from a Single Photo

MetaView has been introduced—a diffusion framework for novel view synthesis from a single image while preserving metric scale. MetaView addresses the critical problem of scale mismatch and geometric inconsistency during large viewpoint changes by combining the power of diffusion models (MM-DiT) with precise geometric cues without the need for heavy 3D reconstruction.

Read briefRead longformTelegram
Keeping teams on one AI harness

Managing AI Agents via a Unified Harness

An article on Baselane suggests using versioned harness.json manifests to solve the problem of AI agent configuration drift within teams. Moving from scattered instructions to centralized management via manifests reduces operational risks and increases transparency of AI usage across the company.

Read briefRead longformTelegram
Meta Oversight Board: AI may be most perfect propaganda machine ever invented

AI as the Perfect Propaganda Machine

The Meta Oversight Board has warned that modern AI models could become powerful propaganda tools due to their tendency toward censorship in certain regions. Developers need to implement multilingual audits and account for the risks of political pressure when fine-tuning models.

Read briefRead longformTelegram

Read the context behind the news.

Explainers collect what happened, why it matters, what changed, source links, related stories, and language editions in one readable page.

See the systems behind the publication.

These projects show how the news pipeline, planning tools, MCP integrations, QGIS tooling, video-editor copilot work, and deployment experiments are built in public.

Production

TG-NEWS

Telegram-first AI news pipeline with discovery, story mapping, publication transactions, and channel output.

AI newsTelegramPipeline
Public OSS

Task-Plan v2 Dashboard

Dashboard for structured multi-agent task plans, implementation gates, review state, and execution visibility.

AgentsDashboardOSS
Public OSS

Mouse Trail Masking Reveal

Two Agent Skills for validating image layers and building a soft cursor-trail canvas reveal hero with tuning controls and browser checks.

CanvasAgent SkillsUX
Public OSS

MCP, QGIS, and editor tools

Public repositories for QGIS agent workflows, OpenCut copilot work, Telegram and Threads MCP servers, research search, and model deployment experiments.

MCPQGISOpenCut

Follow the public channels.

Sergey Kostenchuk

Sergey Kostenchuk / mlllm

I build AI news infrastructure, Telegram automation, local knowledge workflows, and agentic developer tools. mlllm.io is the public surface for that work: a news desk, article archive, blog, project index, and collaboration profile in one coherent system.

The goal is simple: keep useful public pages, visible source trails, related projects, and multilingual editions in one place readers and agents can understand.