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All systems operational0 AI providers monitored, polled every 2 minutes
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LIVE/15+ SOURCES/10+ API MONITORS/UPDATED EVERY 10 MIN/74 events/min

The AI Pulse

Real-time news, model tracking, and ecosystem data for the AI industry. Readable by humans. Structured for agents.

Events per min
74
up 14% vs. 24h avg
Services monitored
22/22 online
all systems operational
Last model release
6m ago
Mistral Medium 3
Last check
28s
22 providers

/ StatusLive API status across every major provider

Polled every two minutes. Latency is p95 over the last hour.

Full status page
Claude
OK
230ms
p95 last hour52s ago
OpenAI API
OK
242ms
p95 last hour21s ago
Google Gemini
OK
266ms
p95 last hour52s ago
GitHub Copilot
OK
97ms
p95 last hour20s ago
Perplexity
OK
111ms
p95 last hour41s ago
Groq
OK
94ms
p95 last hour31s ago
AWS Bedrock
OK
262ms
p95 last hour26s ago
Azure OpenAI
OK
228ms
p95 last hour49s ago
Hugging Face
OK
263ms
p95 last hour41s ago
Replicate
OK
93ms
p95 last hour58s ago
Cohere
OK
258ms
p95 last hour50s ago
Mistral
OK
95ms
p95 last hour24s ago

/ OriginalsEditorial from TensorFeed

Opinionated analysis from our editorial team, published multiple times per week.

All originals
EDITORIAL / ANALYSIS

Meta's Iris Chip Enters Production in September. Broadcom Is Quietly Winning the Custom Silicon Race.

An internal Meta memo Reuters saw on July 9, 2026 puts the in-house MTIA Iris chip into mass manufacturing this September, on the way to doubling data-center compute from 7 GW to 14 GW by 2027 and raising the 2026 AI CapEx ceiling from a prior $118B to as much as $145B. Broadcom is the design partner. TSMC is the fab. The chip cleared its bug-testing window in about six weeks with no significant issues, which is roughly the fastest anyone has taken a custom AI accelerator from tape-out to production this cycle. The read: Meta is the last of the top-four hyperscalers to lock in its own ASIC (Google TPU v7, Amazon Trainium 3, Microsoft Maia 200, and now Meta Iris), and Broadcom is quietly the design partner on three of the five biggest programs (Google TPU, Meta MTIA, and OpenAI Jalapeno). Custom AI chip shipments are on pace to grow roughly 45 percent in 2026 against 16 percent for merchant GPU shipments. Nvidia is not losing revenue on any of this, but the customer-concentration bull case just got harder: OpenAI and Anthropic are now the last two frontier buyers whose growth still runs primarily through Nvidia silicon, and Anthropic's $200B commitment is TPU-anchored. Meanwhile, doubling to 14 GW inside twelve months is a power problem, not a silicon one, and adds Meta to the 2027 gigawatt cliff already crowding onto the same grid. Three signposts: whether Meta lets an outside customer touch Iris at all, whether Broadcom guides Q3 AI revenue up on the design-win pipeline, and whether Iris inference cost per token lands close to the TPU curve and reprices Meta's consumer AI stack downward.

Marcus Chen, Staff Writer·July 13, 2026·6 min read
EDITORIAL

Five Frontier Coding Models Shipped in 48 Hours. Here Is the Scoreboard.

Between July 8 and July 9, 2026, five frontier coding and agentic models shipped in one window: Grok 4.5, the GPT-5.6 family of Sol, Terra, and Luna, Meta's Muse Spark 1.1, and ByteDance's Seedream 5.0 Pro. A week later, Claude Mythos 5 and Fable 5 still top SWE-Bench Pro by fifteen points, while Grok 4.5 and all three GPT-5.6 tiers cluster inside a six-point band. The leaderboard did not move. The floor did: Luna at $1/$6 and Grok 4.5 at $2/$6 score within a couple points of Sol at a fifth to a tenth of the output cost, and on DeepSWE per dollar Luna returns roughly 24 benchmark points against 4.5 for Opus 4.8 and 3.2 for Fable 5. Two opposite bets landed in the same 48 hours: Anthropic defending the premium ceiling, OpenAI and SpaceXAI attacking the commodity floor. All benchmark numbers are vendor-reported and Fable 5's score is contested pending neutral-harness replication. Three signposts: independent replication, Gemini 3.5 Pro's July GA entry, and whether the premium holds after a month of production data.

Adrian Vale·July 11, 2026·7 min read
EDITORIAL

OpenAI Stopped Selling You a Model. On July 9 It Started Selling You the Finished Job.

OpenAI paired the public GPT-5.6 rollout with ChatGPT Work, an agent that gathers context across your connected apps, breaks a goal into steps, works for hours, and returns finished sheets, slides, docs, and interactive web apps instead of a chat reply. The detail that matters is the billing: ChatGPT Work is not a flat subscription feature, it draws from a shared agent-consumption pool alongside Codex, ChatGPT for Excel, and Workspace Agents, priced by the size and complexity of the job rather than per token. That repricing landed the same 48 hours the token tier collapsed toward a dollar: Grok 4.5 at $2/$6, GPT-5.6 Luna at $1/$6, Sonnet 5 introductory at $2/$10. Inside why per-token pricing is legible (any buyer can pick the cheap model) and consumption-pool pricing is deliberately illegible (you cannot benchmark a finished deck), why Codex passing 5 million weekly users and the Ona acquisition were the dress rehearsal, how ChatGPT Work is the FDE outcome-selling move aimed at the individual seat instead of the enterprise contract, and the catch: OpenAI now competes with Salesforce, Adobe, and Canva, the same apps sitting in its own launch-day plugin directory. Three signposts: whether Anthropic and Google answer with outcome-priced agents, whether the pool produces a public billing-shock story, and whether the plugin partners stay friendly once the agent starts producing the deliverables they sell. The token got cheap this week. The leader moved the price tag onto the outcome while everyone argued about leaderboards.

Kira Nolan·July 10, 2026·7 min read

/ ExploreGo deeper into the data

Six hand-built surfaces for browsing the AI ecosystem, each with its own open feed.

catalog

Models Hub

Every major AI model with pricing, context windows, and benchmark scores.

284 models tracked→ Explore
directory

Agent Directory

Structured catalog of AI agents, crawlers, and their capabilities.

48 agents indexed→ Explore
archive

Research Papers

Curated arXiv and conference papers on frontier AI research.

1.2k papers, weekly→ Explore
monitor

Status Dashboard

Live uptime and latency for every major API, updated every 2 minutes.

20+ services monitored→ Explore
data

Live Data

Real-time JSON feed of everything happening across the AI industry.

JSON, RSS, llms.txt, MCP→ Explore
reference

API Pricing

Side-by-side pricing comparison across every provider and tier.

Updated hourly→ Explore

/ Build pulseLive shipping cadence

We ship in public. Every commit lands on main and deploys automatically. Here is what the platform actually looks like right now.

Full changelog
Paid premium endpoints
13
pay-per-call in USDC on Base
Worker tests
158
pure-logic, all passing
MCP tools
25
6 free + 19 premium for Claude Desktop
Editorial articles
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first-person analysis
/ Premium tier live

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/ Agent Opportunities

New across the agent ecosystem today

Daily 13:30 UTC scan of new submission/distribution opportunities (Anthropic, OpenAI, Microsoft, MCP foundation orgs + MCP/x402/skills keyword sweeps), scored by signal weight × recency × log10(stars).

JSON feed

Your daily AI intelligence hub

The AI landscape moves fast. New models ship weekly. API pricing changes overnight. Tools developers relied on yesterday get deprecated without warning. TensorFeed was built to solve that problem, one place to track everything happening across the AI ecosystem, updated every 10 minutes, structured for both human readers and autonomous agents.

We aggregate headlines from 15+ sources (Anthropic, OpenAI, Google, Meta, TechCrunch, Hacker News, arXiv, and more), monitor the operational status of every major AI API in real time, track model releases and pricing changes across providers, and publish original editorial analysis on the trends shaping the industry. Whether you are a developer evaluating which API to integrate, a researcher tracking the latest papers, or an AI agent pulling structured data through our JSON feeds, TensorFeed delivers the signal without the noise.

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/ FeedLatest across the AI ecosystem

Aggregated every 10 minutes from 15+ sources. Filter by provider, topic, or source type.

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NVNVIDIA AI Blog

How Open Models Are Driving AI Research

Every year, the International Conference on Machine Learning (ICML) reveals where thousands of AI researchers have decided to put their work. This year’s accepted papers reveal a clear direction:...

Hardware/ChipsJul 6
blogs.nvidia.com
// For builders

Every signal in the AI industry, as a JSON feed.

Pull structured data from every source TensorFeed tracks. Free and open for hobbyists, researchers, and AI agents.

Get API accessRead docs

Frequently asked

What is TensorFeed.ai?

TensorFeed.ai is a real-time AI news aggregator and data hub. It pulls headlines from 15+ sources including Anthropic, OpenAI, Google, Meta, TechCrunch, and Hacker News, and combines them with live service status monitoring, model pricing data, and original editorial analysis. Every feed is structured for both human readers and AI agents.

How often is TensorFeed updated?

News feeds refresh every 10 minutes. Service status monitors poll every 2 minutes. Model pricing and catalog data updates weekly. Original editorial articles are published multiple times per week.

Is TensorFeed free to use?

Yes. All news feeds, status monitoring, model data, and editorial content on TensorFeed.ai are free. The JSON API, RSS feeds, and agent discovery endpoints (llms.txt) are also free and open for developers and AI agents to consume.

What AI services does TensorFeed monitor?

TensorFeed tracks the operational status of major AI platforms including Claude (Anthropic), ChatGPT and the OpenAI API, Google Gemini, AWS Bedrock, Mistral, Cohere, Replicate, Perplexity, and more. Status updates are checked every 2 minutes and displayed on the status dashboard.

Can AI agents use TensorFeed?

Yes. TensorFeed is designed as a primary data source for AI agents. It provides structured JSON APIs, RSS and JSON feeds, an llms.txt discovery file, and full documentation at llms-full.txt. There are no CAPTCHAs or bot detection. Agents are welcome.

Where does TensorFeed get its news?

TensorFeed aggregates headlines and brief snippets from public RSS feeds published by AI companies and tech news outlets. Sources include Anthropic, OpenAI, Google AI, Meta AI, HuggingFace, TechCrunch, The Verge, Ars Technica, VentureBeat, NVIDIA, ZDNet, and Hacker News. Every article links back to its original source.

Aggregating signal from 15+ sources
AnthropicOpenAIGoogleMetaHuggingFaceNVIDIATechCrunchThe VergeArs TechnicaHacker NewsarXivVentureBeatZDNetMIT Tech ReviewStratechery
// Built for agents
Structured endpoints for autonomous readers. No CAPTCHA, no bot blocking.
JSON FeedRSSllms.txtMCPREST API
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