Anthropic commits $10 million to Canadian AI research across eight institutions


TL;DR

Anthropic committed $10M CAD to eight Canadian institutions for AI research. Canada ranks second globally in per-capita Claude usage. Startups get $5K API credits.

Anthropic is committing $10 million CAD to eight Canadian research institutions to fund work on beneficial and responsible AI applications. The partnerships span Canada’s three leading regional AI institutes, Amii in Edmonton, Mila in Montréal, and the Vector Institute in Toronto, along with children’s hospital CHEO, the Centre for Addiction and Mental Health, Université Laval, the University of Toronto, and the University of Saskatchewan.

The funding covers research areas from reinforcement learning and AI safety to mental health, Indigenous languages, and quantum computing. Mila will use Claude to develop AI assistants that help researchers discover and assess scientific breakthroughs. CAMH’s Krembil Centre for Neuroinformatics will build predictive models for mental health treatment and run fairness evaluations of psychiatric AI systems. Université Laval will study how large language models behave in varied cultural contexts, including Quebec French and Indigenous languages.

Anthropic also published its first Canadian country brief from the Anthropic Economic Index. Canada ranks eighth worldwide in Claude usage but second in per-capita adoption, with Canadians using Claude at more than four times the rate their population predicts. Only the US ranks higher. Usage tracks the local economy: translation requests are highest in provinces with more government workers, reflecting Canada’s bilingualism requirements. British Columbia leads in per-person use, with Ontario close behind. Anthropic committed $200 million to a Gates Foundation partnership in May, and the Canadian investment extends the company’s pattern of building non-commercial relationships alongside its enterprise business.

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This summer, Anthropic will add Amii, Mila, and Vector to its startup programme, giving hundreds of affiliated Canadian startups at least $5,000 USD each in API credits. “Some of the foundations of modern AI came out of Toronto, Montréal, and Edmonton, and so, strikingly, did many of the researchers most committed to making it safe,” said co-founder Chris Olah. Anthropic has been systematically expanding Claude’s presence across enterprise, government, and now academic institutions, building distribution and dependency across every sector simultaneously.



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Recent Reviews


YouTube has an AI slop problem, and its crackdown is catching legitimate creators in the crossfire. Faceless channels, where no human host ever appears on screen, have existed for years and are not inherently AI-generated.

Many are run by solo creators who simply prefer to stay anonymous. The problem is that AI tools made it easy to flood the platform with low-effort faceless content at scale, and YouTube’s algorithm is now penalizing the format as a whole.

How bad is the AI slop problem on YouTube?

A Kapwing study found that roughly 21% of the first 500 videos recommended to a new YouTube account were classified as AI slop, while 33% fell into a broader brainrot category. The problem extends to children, too, as more than 40% of YouTube Shorts recommended to kids in a 15-minute session contained low-quality AI content.

YouTube’s response has been to tweak its algorithm to favor videos with real human faces on camera, which is hitting faceless creators even when their content is entirely human-made.

How is YouTube tackling its AI slop problem?

YouTube is now testing a new pop-up on mobile that asks viewers to rate whether a video feels like AI slop, on a scale from “not at all” to “extremely.” The idea sounds reasonable, but crowdsourcing AI detection has real problems. People are bad at spotting AI content, and they are getting worse at it as AI capabilities continue to improve.

There are also legitimate concerns that YouTube could use this viewer feedback as training data for its own AI models, potentially making future AI-generated content even harder to spot.

🚨 Did you just see what YouTube did?

YouTube isn’t banning AI slop.. They’re making you label it so they can train their next model to not look like slop.

Read that again…

You flag the bad AI content. YouTube collects it. Google feeds it into Veo 4… Then next year their… https://t.co/8UC2J3mjjv pic.twitter.com/mIrTChqC1b

— Tuki (@TukiFromKL) March 17, 2026

Meanwhile, faceless creators are scrambling to adapt. According to The Hollywood Reporter, some are hiring cheap on-camera hosts through platforms like Fiverr and Upwork. Others are doubling down on niche educational content, which has held up better than broad content farms.

The AI text-to-video space is still valued at enormous sums, with Higgsfield AI alone sitting at $1 billion, but on YouTube, the math for faceless creators is getting harder to work out every month.



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