Hold on tight, folks, because THIS week on ThursdAI felt like riding a roller coaster through the wild world of open-source AI - extreme highs, mind-bending twists, and a sprinkle of "wtf is happening?" conspiracy theories for good measure. 😂 Theme of this week is, Open Source keeps beating GPT-4, while we're inching towards intelligence too cheap to meter on the API fronts. We even had a live demo so epic, folks at the Large Hadron Collider are taking notice! Plus, strawberry shenanigans abound (did Sam REALLY tease GPT-5?), and your favorite AI evangelist nearly got canceled on X! Buckle up; this is gonna be another long one! 🚀 Qwen2-Math Drops a KNOWLEDGE BOMB: Open Source Wins AGAIN! When I say "open source AI is unstoppable", I MEAN IT. This week, the brilliant minds from Alibaba's Qwen team decided to show everyone how it's DONE. Say hello to Qwen2-Math-72B-Instruct - a specialized language model SO GOOD at math, it's achieving a ridiculous 84 points on the MATH benchmark. 🤯 For context, folks... that's beating GPT-4, Claude Sonnet 3.5, and Gemini 1.5 Pro. We're not talking incremental improvements here - this is a full-blown DOMINANCE of the field, and you can download and use it right now. 🔥 Get Qwen-2 Math from HuggingFace here What made this announcement EXTRA special was that Junyang Lin , the Chief Evangelist Officer at Alibaba Qwen team, joined ThursdAI moments after they released it, giving us a behind-the-scenes peek at the effort involved. Talk about being in the RIGHT place at the RIGHT time! 😂 They painstakingly crafted a massive, math-specific training dataset, incorporating techniques like Chain-of-Thought reasoning (where the model thinks step-by-step) to unlock this insane level of mathematical intelligence. "We have constructed a lot of data with the form of ... Chain of Thought ... And we find that it's actually very effective. And for the post-training, we have done a lot with rejection sampling to create a lot of data sets, so the model can learn how to generate the correct answers" - Junyang Lin Now I gotta give mad props to Qwen for going beyond just raw performance - they're open-sourcing this beast under an Apache 2.0 license, meaning you're FREE to use it, fine-tune it, adapt it to your wildest mathematical needs! 🎉 But hold on... the awesomeness doesn't stop there! Remember those smaller, resource-friendly LLMs everyone's obsessed with these days? Well, Qwen released 7B and even 1.5B versions of Qwen-2 Math, achieving jaw-dropping scores for their size (70 for the 1.5B?? That's unheard of!).🤯 Nisten nearly lost his mind when he heard that - and trust me, he's seen things. 😂 "This is insane! This is... what, Sonnet 3.5 gets what, 71? 72? This gets 70? And it's a 1.5B? Like I could run that on someone's watch. Real." - Nisten With this level of efficiency, we're talking about AI-powered calculators, tutoring apps, research tools that run smoothly on everyday devices. The potential applications are endless! MiniCPM-V 2.6: A Pocket-Sized GPT-4 Vision... Seriously! 🤯 If Qwen's Math marvel wasn't enough open-source goodness for ya, OpenBMB had to get in on the fun too! This time, they're bringing the 🔥 to vision with MiniCPM-V 2.6 - a ridiculous 8 billion parameter VLM (visual language model) that packs a serious punch, even outperforming GPT-4 Vision on OCR benchmarks! OpenBMB drops a bomb on X here I'll say this straight up: talking about vision models in a TEXT-based post is hard. You gotta SEE it to believe it. But folks... TRUST ME on this one. This model is mind-blowing, capable of analyzing single images, multi-image sequences, and EVEN VIDEOS with an accuracy that rivaled my wildest hopes for open-source.🤯 Check out their playground and prepare to be stunned It even captured every single nuance in this viral toddler speed-running video I threw at it, with an accuracy I haven't seen in models THIS small: "The video captures a young ch