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AI can now spot tiny traces of cancer from just a drop of blood, in minutes, and it costs less than your lunch. It’s already being tested on real patients. Do you believe how it works?
What are on FIRE 🔥
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AI INSIGHTS
Imagine detecting cancer before it causes any symptoms, using just a small tube of blood, and paying less than the price of dinner for it. Researchers at A*STAR in Singapore have developed Fragle, an AI-powered tool that detects tiny traces of cancer in blood samples.
🔍 What Fragle Actually Does → detect circulating tumor DNA (ctDNA), tiny DNA fragments from cancer cells that float in the blood. Because ctDNA tends to break into different sizes than healthy DNA, Fragle can tell them apart.
→ It gives doctors an early warning system for cancer relapse or treatment failure.
🧪 How It Was Tested → Researchers trained it on whole-genome sequencing data from both cancer patients and healthy individuals. It’s already being used in clinical trials with over 100 patients undergoing cancer treatment in Singapore.
A typical ctDNA test today can cost up to $780. BUT, Fragle’s method costs just $39. That low cost unlocks frequent monitoring → it’s like a live feed.
Fragle was built with adoption in mind:
It integrates seamlessly with standard DNA profiling labs.
No need for new machines or massive training, just plug and play.
Doctors can use it alongside existing tools, making it easy to roll out.
Why It Matters: At just $39, this tech could finally make high-quality cancer monitoring accessible worldwide, not just for rich countries or private hospitals. And if this becomes the norm, expect a future where cancer detection is as routine as a cholesterol check.
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TODAY IN AI
AI HIGHLIGHTS
🎓 Anthropic released a Free 12-lesson "AI Fluency" course, and it goes way beyond basic prompting tips. You'll plan and execute a real project. You get a certificate at the end. Join here.
🧠 v0’s captcha contest to build “the most ridiculous captcha” is absolutely unhinged. Submissions include: “Are you human? Or are you dancer?”. Winner gets $1000 credits.
💥 It turns out, you can combine Claude Code + OpenAI o3 + Gemini 2.5 all working together through MCP like The Avengers. A builder just gave a quick guide to do it. See it here.
🗑️ ChatGPT polluted the internet so badly that it's hobbling future AI development. Model collapse is real, AI spam has tainted modern data. Pre-2022 data is now gold.
🤺 Claude 4 just helped co-author a spicy takedown of Apple’s viral “LLMs can’t reason” paper, basically said, “nice try, but it’s kinda sucked”. AI beef is peer-reviewed.
💰 AI Daily Fundraising: AI venture studio has raised $190 million to create innovative AI tools for various industries, with a focus on healthcare & finance. This investment highlights AI's growing significance.
AI SOURCES FROM AI FIRE
🔥 Ep 11 Weekly ToolDrop: 4 Trending & Must-Have Git Tools This Week:
High-performance photo management
Awesome lists – Basically the internet’s favorite rabbit hole
The platform to build like a team of hundreds
Personal AI assistant framework
Note: These exclusive resources & reviews are available only in our AI Fire community. It’s because you guys can freely ask for support or share personal experience during testing there. Get your full breakdown here (no hidden fee)!
NEW EMPOWERED AI TOOLS
🎬 SeedancePro creates professional videos instantly from texts or images.
🧩 Instance turns your simple ideas into functional apps, games, websites.
🗣️ Fluidworks talks to each user in session, personalizes every journey.
✨ Wonderish builds stunning pages, apps with zero coding experience.
📝 Scribe records your screen & turns into detailed guide with screenshots.
AI QUICK HITS
✨ ChatGPT’s Canvas now supports downloads as PDFs, docs,… Try it here.
🤯 A short film by Google Veo & director Darren premiered at Tribeca Festival. Full movie here.
💸 A woman won $10K in a ML comp in 1 week. Here’s her full strategy.
⚠ The cracks in the OpenAI-Microsoft relationship are reportedly widening.
🧨 OpenAI bagged a $200M deal with the U.S. military to join war game.
AI CHART
MIT just taught AI called SEAL (Self-Adapting LLMs) how to teach itself and it’s already outperforming GPT-4.1 in some tasks using its own notes.
→ It’s a framework that lets an LLM train itself by creating its own synthetic data, update instructions, and weight adjustments.
SEAL allows models to generate their own "self-edits" - instructions for creating data and setting parameters to update their own weights.
In certain knowledge tasks, the model learned more effectively from its own notes than from materials generated by GPT-4.1.
→ This hints that the model is capable of adapting its learning to its own style and needs, a bit like how humans learn best from their own revision notes.
The system also dramatically improved at puzzle-solving tasks, jumping from 0% with standard methods to 72.5% after learning how to train itself effectively.
SEAL and similar frameworks (like Sakana’s Dynamic Graph Models/DGM) are exploring the idea of LLMs that evolve continuously without being retrained by humans. This is the kind of mechanism often theorized in discussions about AGI or even superintelligence.
AI JOBS
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