Artificial intelligenceReading guide · 5 min
Where to follow AI news: a source list with a purpose
The short answerUse a small mix of sources: a digest for discovery, original announcements for release details, research papers for methods and model cards for documented limits. Keep robotics in the mix if physical applications interest you. No single feed provides the complete picture.
A good source list is not another endless feed
You do not need to visit every destination on this page every morning. Think of them as different shelves in a reference library. A briefing can tell you which story deserves attention; the relevant shelf helps you answer the next question.
For example, ‘a model is now available’ sends you to a release announcement. ‘It outperformed the previous method’ sends you to a paper or evaluation. ‘Can I use it with my documents?’ sends you to the specific product documentation and data policy. One source is not automatically qualified to answer all three.
For new AI research: arXiv's AI submissions
The arXiv artificial intelligence listing is a direct route to recent research submissions, with titles, authors, dates and links to the papers. Use it when you want to identify the actual work behind a research headline. The AI category is one starting point, not every AI-related paper on the service.
Our suggested method is to search for the paper title you already care about, read the abstract and find the evaluation and limitations. Check version dates and any stated publication venue. A paper being available on arXiv is not, by itself, proof that its claims have passed peer review or been independently reproduced. Source: arXiv: recent artificial intelligence submissions
For robot learning and demos: arXiv's robotics submissions
The robotics listing is useful when your interests extend beyond chatbots: manipulation, navigation, robot learning and the systems that connect perception to action. It exposes recent submissions without requiring you to rely on the shortest social-media clip.
Once you find a paper, look for an author-linked project page with demonstration videos. Then return to the paper to check the task setup, autonomy and trial counts. Do not treat a link from an unrelated repost as proof that you are watching the authors' original footage. Source: arXiv: recent robotics submissions
For releases and availability: the company's own newsroom
Anthropic's newsroom is one example of a primary announcement feed. It is useful for finding the company's description of a release and following links into the associated material. Other providers' official newsrooms serve the same role for their own systems.
Treat a newsroom as a first-party account, not an independent verdict on who is winning. Record the exact model or product, the announcement date and whether access is a preview, waitlist or general release. Keep separate notes for what was announced and what you personally verified. Source: Anthropic: newsroom
For the link between AI and robotics: research-lab updates
Google DeepMind's news section spans model research and physical-world applications. It can help you follow a research story into a project, paper or technical explanation. Start with the linked work when you need to understand a specific claim.
The same perspective check applies here: a laboratory is explaining its own work. A compelling announcement is a reason to inspect the evidence, not a replacement for it. For an important result, look for later evaluations or reproductions that test the boundary the announcement leaves open. Source: Google DeepMind: news
For intended uses and limitations: model cards
Hugging Face's model-card documentation explains the role of a model's accompanying description, including uses, limitations, training and evaluation information. When a model is hosted there, check the card for that exact release rather than a similarly named repository.
A missing field is not a favourable answer. If the card says nothing about the language or task you need, leave the question unresolved. This is also where a useful news summary should slow down: availability and suitability are different things. Source: Hugging Face: model cards
How to check whether an AI news source supports the claim
Use this four-line note: claim, original source, evidence, unanswered question. For an invented example, ‘a robot sorts unfamiliar mugs’ needs more than a clip of one familiar mug. The useful source would describe which objects were unfamiliar and how the task was evaluated. If it does not, keep that part of the claim unresolved.
A link that opens is not the same as a citation that supports the sentence. Check the exact wording, the date and whether the source is a company announcement, a research result or an independent evaluation. You can stop once the question you came with is answered; source-checking does not require reading every related paper.
Turn the list into a manageable AI news routine
Pick one place to discover stories and open an original source only when a claim interests you. Save a short note with the date, what changed, the supporting link and the unresolved question. This gives you context you can revisit without rebuilding an entire timeline.
Suppose you see three posts about the same robot. Before saving all three, check whether they point to one underlying demonstration. Conversely, a later deployment announcement may be a genuine new development even if the robot's name is familiar. Follow changes, not just names or repetition.
Read The Day is one way to get that starting point in your inbox. If you prefer building your own reading list, use the sources here directly. The aim is the same: understand the interesting part, know what supports it and finish reading with some of your morning left.
Match the question to the source
- What happened? Find the dated original announcement.
- What was tested? Find the paper and evaluation setup.
- Can I use it? Read the actual access instructions.
- What are the limits? Check documentation for the exact release.
- Is this a new development? Compare it with the earlier source.
Go to the evidence
Sources and further reading
- arXiv: recent artificial intelligence submissions
Primary research discovery listing; the guide does not endorse every listed claim.
- arXiv: recent robotics submissions
Direct route to robotics papers and author-provided project links.
- Anthropic: newsroom
A first-party announcement source, not independent comparative evidence.
- Google DeepMind: news
A first-party research and product news source.
- Hugging Face: model cards
Documentation for finding model-specific uses, limitations and evaluation information.
An AI-assisted editorial guide. This is a selective source map, not an exhaustive list or a claim that all linked research is verified. Destinations checked 13 September 2026; the reading workflow is our recommendation. Our editorial standards.