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Florent Daudens

fdaudens

AI & ML interests

AI & Journalism

Recent Activity

liked a model about 24 hours ago

Qwen/QwQ-32B-GGUF

posted an update 1 day ago

I read the 456-page AI Index report so you don't have to (kidding). The wild part? While AI gets ridiculously more accessible, the power gap is actually widening: 1️⃣ The democratization of AI capabilities is accelerating rapidly: - The gap between open and closed models is basically closed: difference in benchmarks like MMLU and HumanEval shrunk to just 1.7% in 2024 - The cost to run GPT-3.5-level performance dropped 280x in 2 years - Model size is shrinking while maintaining performance - Phi-3-mini hitting 60%+ MMLU at fraction of parameters of early models like PaLM 2️⃣ But we're seeing concerning divides deepening: - Geographic: US private investment ($109B) dwarfs everyone else - 12x China's $9.3B - Research concentration: US and China dominate highly-cited papers (50 and 34 respectively in 2023), while next closest is only 7 - Gender: Major gaps in AI skill penetration rates - US shows 2.39 vs 1.71 male/female ratio The tech is getting more accessible but the benefits aren't being distributed evenly. Worth thinking about as these tools become more central to the economy. Give it a read - fascinating portrait of where AI is heading! https://hai-production.s3.amazonaws.com/files/hai_ai_index_report_2025.pdf

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fdaudens's activity

posted an update 1 day ago

Post

1669

I read the 456-page AI Index report so you don't have to (kidding). The wild part? While AI gets ridiculously more accessible, the power gap is actually widening:

1️⃣ The democratization of AI capabilities is accelerating rapidly:
- The gap between open and closed models is basically closed: difference in benchmarks like MMLU and HumanEval shrunk to just 1.7% in 2024
- The cost to run GPT-3.5-level performance dropped 280x in 2 years
- Model size is shrinking while maintaining performance - Phi-3-mini hitting 60%+ MMLU at fraction of parameters of early models like PaLM

2️⃣ But we're seeing concerning divides deepening:
- Geographic: US private investment ($109B) dwarfs everyone else - 12x China's $9.3B
- Research concentration: US and China dominate highly-cited papers (50 and 34 respectively in 2023), while next closest is only 7
- Gender: Major gaps in AI skill penetration rates - US shows 2.39 vs 1.71 male/female ratio

The tech is getting more accessible but the benefits aren't being distributed evenly. Worth thinking about as these tools become more central to the economy.

Give it a read - fascinating portrait of where AI is heading! https://hai-production.s3.amazonaws.com/files/hai_ai_index_report_2025.pdf

1 reply

posted an update 3 days ago

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See that purple banner on the Llama 4 models? It's Xet storage, and this is actually huge for anyone building with AI models. Let's geek out a little bit 🤓

Current problem: AI models are massive files using Git LFS. But with models getting bigger and downloads exploding, we needed something better.
Xet lets you version large files like code, with compression and deduplication, all Git-compatible. That means less bandwidth, faster sharing, and smoother collaboration.

Real numbers: ~25% deduplication on Llama 4 models, hitting ~40% for finetunes.

Scale matters here - the Hub served 2B model downloads in 30 days, Llama models alone at 60M. The upcoming Llama 4 Behemoth has 2T parameters! Xet's chunk-based system was built exactly for this.

This is the kind of engineering that makes the next wave of large models actually usable. Kudos to the team! 🧨

Check out the models collection: meta-llama/llama-4-67f0c30d9fe03840bc9d0164

reacted to jeffboudier's post with 🚀 3 days ago

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1989

Llama4 is out and Scout is already on the Dell Enterprise Hub to deploy on Dell systems 👉 dell.huggingface.co

reacted to jsulz's post with 🔥 3 days ago

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Huge week for

xet-team as Llama 4 is the first major model on Hugging Face uploaded with Xet providing the backing! Every byte downloaded comes through our infrastructure.

Using Xet on Hugging Face is the fastest way to download and iterate on open source models and we've proved it with Llama 4 giving a boost of ~25% across all models.

We expect builders on the Hub to see even more improvements, helping power innovation across the community.

With the models on our infrastructure, we can peer in and see how well our dedupe performs across the Llama 4 family. On average, we're seeing ~25% dedupe, providing huge savings to the community who iterate on these state-of-the-art models. The attached image shows a few selected models and how they perform on Xet.

Thanks to the

meta-llama team for launching on Xet!

posted an update 4 days ago

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"Am I going to be replaced by AI?" - Crucial question, but maybe we're asking the wrong one.

📈 There's a statistic from my reads this week that stays with me: Tomer Cohen, LinkedIn's CPO, shares to Jeremy Kahn that 70% of skills used in most jobs will change by 2030. Not jobs disappearing, but transforming. And he calls out bad leadership: "If in one year's time, you are disappointed that your workforce is not 'AI native,' it is your fault."

🔄 Apparently, the Great Recalibration has begun. We're now heading into an era where AI is fundamentally redefining the nature of work itself, by forcing a complete reassessment of human value in the workplace, according to a piece in Fast Company. But it might be driven more by "the need for humans to change the way they work" than AI.

⚡ The Washington Post draws a crucial parallel: We're facing an "AI shock" similar to manufacturing's "China shock" - but hitting knowledge workers. Especially entry-level, white-collar work could get automated. The key difference? "Winning the AI tech competition with other countries won't be enough. It's equally vital to win the battle to re-skill workers."

Digging into these big questions in this week’s AI in the News: https://fdaudens.substack.com/publish/posts/detail/160596301

Also, I'm curious: how are you keeping up with this pace of change? What strategies are working for you?

posted an update 6 days ago

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Did we just drop personalized AI evaluation?! This tool auto-generates custom benchmarks on your docs to test which models are the best.

Most benchmarks test general capabilities, but what matters is how models handle your data and tasks. YourBench helps answer critical questions like:
- Do you really need a hundreds-of-billions-parameter model sledgehammer to crack a nut?
- Could a smaller, fine-tuned model work better?
- How well do different models understand your domain?

Some cool features:
📚 Generates custom benchmarks from your own documents (PDFs, Word, HTML)
🎯 Tests models on real tasks, not just general capabilities
🔄 Supports multiple models for different pipeline stages
🧠 Generate both single-hop and multi-hop questions
🔍 Evaluate top models and deploy leaderboards instantly
💰 Full cost analysis to optimize for your budget
🛠️ Fully configurable via a single YAML file

26 SOTA models tested for question generation. Interesting finding: Qwen2.5 32B leads in question diversity, while smaller Qwen models and Gemini 2.0 Flash offer great value for cost.

You can also run it locally on any models you want.

I'm impressed. Try it out: yourbench/demo

posted an update 8 days ago

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🔥 DeepSeek vibe coding with DeepSite is going viral with awesome projects!

From games to stunning visualizations, 7 wild examples:

📺 AI TV with custom channels and animations https://x.com/_akhaliq/status/1905747381951545647

🚀 Earth to Moon spacecraft journey visualization
Watch this incredible Three.js space simulation with zero external assets:
https://x.com/_akhaliq/status/1905836902533451999

💣 Minesweeper in 2.5 minutes! Built & deployed instantly on DeepSite. Zero setup needed:
https://x.com/cholf5/status/1906031928937218334

🎮 Asked for Game of Life, got a masterpiece. Simple prompt, complex features. See it in action: https://x.com/pbeyssac/status/1906304454824992844

💫 One-shot anime website with perfect UI. DeepSite turned a simple request into a fully-functional anime site: https://x.com/risphereeditor/status/1905961725028913264

📊 10-minute World Indicators Dashboard. Just described what I wanted and got a full interactive dashboard! https://x.com/i/status/1906345214089785634

✨ Ready to build without coding? Imagine it. Build it. Share it! enzostvs/deepsite

posted an update 9 days ago

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Want to vibecode with DeepSeek? Just spent 10 minutes with this space and created a full world indicators dashboard - literally just by describing what I wanted!

Anyone can now prototype and deploy projects instantly.

Try out the app: enzostvs/deepsite

My dashboard: fdaudens/world-indicators

posted an update 12 days ago

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Want to ramp up your AI skills and start breaking bigger stories? With the Journalists on Hugging Face community, we're launching our first learn-together course!

We'll build AI classifiers that process months of data in minutes. How?

- Work through an interactive version of an excellent course developed by Ben Welsh and Derek Willis
- Share findings and get help in our dedicated community channel
- Build working classifiers you can use in your reporting today

No coding background needed - if you can write a ChatGPT or Claude prompt, you can do this. Journalists are already using these techniques to break stories, from uncovering hidden real estate deals to tracking unusual campaign spending.

Join us—it might give you your next big story!

Thanks to Ben and Derek for letting me adapt their excellent course into this interactive version!

- Check out the course: JournalistsonHF/first-llm-classifier

- Join our Slack community to learn together: https://docs.google.com/forms/d/e/1FAIpQLSfyA7G6Y9q-5hDBSnGc3CFtg9H8fjqKCCuieptXuTqRudGNjQ/viewform

posted an update 18 days ago

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🎥 Just tested Stability AI's Stable Virtual Camera - it turns a single photo into dynamic video with AI-powered camera movements! From static meeting room to cinematic sweeps. 🚀

Try it out: stabilityai/stable-virtual-camera

posted an update 20 days ago

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🔊 Meet Orpheus: A breakthrough open-source TTS model that matches human-level speech with empathy & emotion.
- Available in 4 sizes (150M-3B parameters)
- delivers ultra-fast streaming
- zero-shot voice cloning.
- Apache 2.0 license

canopylabs/orpheus-tts-67d9ea3f6c05a941c06ad9d2

1 reply

posted an update 21 days ago

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Want to build useful newsroom tools with AI? We’re launching a Hugging Face x Journalism Slack channel where journalists turn AI concepts into real newsroom solutions.

Inside the community:
✅ Build open-source AI tools for journalism
✅ Get direct help from the community
✅ Stay updated on new models and datasets
✅ Learn from other journalists’ experiments and builds

The goal? Go from “I read about AI” to “I built an AI tool that supercharged my newsroom.” —no more learning in isolation.

Join us! https://join.slack.com/t/journalistson-tnd8294/shared_invite/zt-30vsmhk4w-dZpeMOoxdhCvfNsqtspPUQ (Please make sure to use a clear identity—no teddybear85, for example 😉)

(If you know people who might be interested, tag them below! The more minds we bring in, the better the tools we build.)

posted an update 22 days ago

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Photoshopping will never be the same. Gemini 2.0 Flash in a Gradio app = 🤯

ameerazam08/Gemini-Image-Edit

posted an update 26 days ago

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🤯 Gemma 3's image analysis blew me away!

Tested 2 ways to extract airplane registration numbers from photos with 12B model:

1️⃣ Gradio app w/API link (underrated feature IMO) + ZeroGPU infra on Hugging Face in Google Colab. Fast & free.

2️⃣ LMStudio + local processing (100% private). Running this powerhouse on a MacBook w/16GB RAM is wild! 🚀

Colab: https://colab.research.google.com/drive/1YmmaP0IDEu98CLDppAAK9kbQZ7lFnLZ1?usp=sharing

reacted to clem's post with 🚀 26 days ago

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We just crossed 1,500,000 public models on Hugging Face (and 500k spaces, 330k datasets, 50k papers). One new repository is created every 15 seconds. Congratulations all!

3 replies

posted an update 27 days ago

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Ever wanted 45 min with one of AI’s most fascinating minds? Was with @thomwolf at HumanX Vegas. Sharing my notes of his Q&A with the press—completely changed how I think about AI’s future:

1️⃣ The next wave of successful AI companies won’t be defined by who has the best model but by who builds the most useful real-world solutions. "We all have engines in our cars, but that’s rarely the only reason we buy one. We expect it to work well, and that’s enough. LLMs will be the same."

2️⃣ Big players are pivoting: "Closed-source companies—OpenAI being the first—have largely shifted from LLM announcements to product announcements."

3️⃣ Open source is changing everything: "DeepSeek was open source AI’s ChatGPT moment. Basically, everyone outside the bubble realized you can get a model for free—and it’s just as good as the paid ones."

4️⃣ Product innovation is being democratized: Take Manus, for example—they built a product on top of Anthropic’s models that’s "actually better than Anthropic’s own product for now, in terms of agents." This proves that anyone can build great products with existing models.

We’re entering a "multi-LLM world," where models are becoming commoditized, and all the tools to build are readily available—just look at the flurry of daily new releases on Hugging Face.

Thom's comparison to the internet era is spot-on: "In the beginning you made a lot of money by making websites... but nowadays the huge internet companies are not the companies that built websites. Like Airbnb, Uber, Facebook, they just use the internet as a medium to make something for real life use cases."

Love to hear your thoughts on this shift!

1 reply

posted an update 28 days ago

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🔥The Open R1 team just dropped OlympicCoder and it's wild:

- 7B model outperforms Claude 3.7 Sonnet on IOI benchmark (yes, 7B!!)
- 32B crushes all open-weight models tested, even those 100x larger 🤯

Open-sourcing the future of code reasoning! 🚀

Check it out https://huggingface.co/blog/open-r1/update-3

replied to their post 29 days ago

Yes, exploring a few ideas!

posted an update about 1 month ago

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Honored to be named among their 12 pioneers and power players in the news industry in the 2025 Tech Trends Report from Future Today Strategy Group.

Incredible group to be part of - each person is doing groundbreaking work at the intersection of AI and journalism. Worth following them all: they're consistently sharing practical insights on building the future of news.

Take the time to read this report, it's packed with insights as always. The news & information section's #1 insight hits hard: "The most substantive economic impact of AI to date has been licensing payouts for a handful of big publishers. The competition will start shifting in the year ahead to separate AI 'haves' that have positioned themselves to grow from the 'have-nots.'"

This AI-driven divide is something I've been really concerned about. Now is the time to build more than ever!

👉 Full report here: https://ftsg.com/wp-content/uploads/2025/03/FTSG_2025_TR_FINAL_LINKED.pdf

2 replies

posted an update about 1 month ago

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AI will bring us "a country of yes-men on servers" instead of one of "Einsteins sitting in a data center" if we continue on current trends.

Must-read by @thomwolf deflating overblown AI promises and explaining what real scientific breakthroughs require.

https://thomwolf.io/blog/scientific-ai.html

2 replies