Naqqash Abbassi’s Post

Really glad to see Apple pushing for the on device models. They have just added 𝐓𝐰𝐞𝐧𝐭𝐲 𝐧𝐞𝐰 𝐜𝐨𝐫𝐞𝐌𝐋 models for on-device AI & 𝐟𝐨𝐮𝐫 𝐧𝐞𝐰 𝐝𝐚𝐭𝐚𝐬𝐞𝐭𝐬 on Hugging Face _________________________________ ✅ Follow me Naqqash Abbassi for regular updates and insights on Generative AI and my journey as a CTO in AI product development

2024 marked a pivotal moment in the world of AI 🚀 🔵 The explosion of larger models like Llama 405B, the debut of transformative applications like Mochi 1, and the rise of effective reasoning techniques like Chain of Thought have pushed AI inference to unprecedented heights. 🔵 Compute demand has skyrocketed, with the industry waking up to the urgent need for more efficient compute to solve the AI power provisioning problem. 🔵 A very exciting shift: realtime-oriented applications are taking center stage. The future lies in massively parallelizing models to deliver ultra-low latency, seamless user experiences. For us as a company, 2024 wasn’t just about witnessing these changes. It was about positioning ourselves to help lead them. Swipe through the slideshow to see some of the key moments from our year. Here’s to 2025.

Tencent has just released a new foundational video generation model HunyuanVideo ⤵️ 13B parameters and outperforms several others like Runway, Kling and Haiko on different benchmarks. At least 60 GB VRAM required for the generation. Check here for more details -> https://lnkd.in/dhkMWnAz __________________________________ ♻️ Repost if you find this useful! 🔔 Follow me, Naqqash Abbassi for more on Generative AI and my journey as a Founder and CTO in AI product development.

Artificial Intelligence is at the core of our belief in a different future and our project to build an interplanetary payment system. Our AI website [https://lnkd.in/dZ8kyq_v] highlights our current initiatives in the field and provides a platform for our data scientists and researchers to discuss relevant topics. The latest article, “Bridging Human and Machine Learning: A Pedagogical Perspective on LLMs’ Learning and Hallucinations” [https://lnkd.in/dJTuvNm7], draws parallels between children’s literacy development and LLM hallucinations, exploring the connections between human and machine learning processes. You are invited to techno-philosophize with us. Check out the previous posts as well: • “When Previous Equations Meet Neural Networks” [https://lnkd.in/dA5PcVP4] • “Evolutionary Feature Selection” [https://lnkd.in/dEcKZV_P] • “The Power of Conversational AI and the Future of Innovation” [https://lnkd.in/dvkXpvqn] • "Consciousness, Reasoning and LLMs playing tic-tac-toe: chain-of-thought experiment" [https://lnkd.in/d7DjzjtR] • “Optimizing Advertising Campaigns with Marketing Models”. [https://lnkd.in/dHJB-Hk4]

If you are looking for a small on device based reasoning model you should give SmallThinker a try - this is based on the Qwen2.5-3B-Instruct and performs pretty well. The dataset QWQ-LONGCOT-500K was used to fine tune the model. This dataset was based on the QWQ-32B-Preview model. Good to see that this dataset is also open source. You can test this model locally by using Ollama. Or via link in the comment of the Hugging Face space. The answers are not always correct and sometimes it is pretty verbose however, in general the model is performing pretty well if you consider its size. __________________________________ ♻️ Repost if you find this useful! 🔔 Follow me, Naqqash Abbassi for more on Generative AI and my journey as a Founder and CTO in AI product development.

In this episode: * OpenAI's pitch for a $100 billion data center and AI strategy plan outlines infrastructure and regulatory needs, emphasizing AI's foundational role akin to electricity.  * Google's Gemini model challenges OpenAI's dominance, showing strong performance in chatbot arenas alongside generative AI advancements.  * DeepMind's AlphaFold3 gets open-sourced for academic use, while new chips from NVIDIA and Google show significant performance boosts.  * Anthropic and TSMC updates highlight strategic funding, regulation influences, and the complex dynamics of AI hardware and international policy.

If you were watching Yahoo! Finance’s recent segment on how different industry verticals are integrating GenAI, you may have seen some familiar data pop up. Your eyes were not deceiving you! BCG’s recent AI executive perspective, CEO’s Guide to Maximizing Value Potential from AI in 2024, was indeed heavily featured – grounding anecdotes from executives at JP Morgan, Alphabet, and more, in our survey outputs. How cool is that? Make sure to watch the clip below (BCG data starts at 2:30) to see our work in action!

𝗔𝗚𝗜 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗱 ? I’m still trying to wrap my head around the news that just dropped, OpenAI’s 𝗢𝟯 model (which, fun fact, is actually their second iteration) might’ve just reshaped our understanding of AI progress. It seems that this model has pulled off something many believed was years away, it outperformed humans on the Arc benchmark, a notoriously tough and 𝗺𝗲𝗺𝗼𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻-𝗿𝗲𝘀𝗶𝘀𝘁𝗮𝗻𝘁 test designed to evaluate real reasoning and problem-solving. The fact that a system can learn novel tasks on the fly, tasks that even a child can handle with basic 𝗰𝗼𝗿𝗲 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲, marks a huge leap from the usual pattern-based AIs we’ve grown accustomed to. On the demo, I find it wild that 03 apparently costs an astronomical sum to run for more complex tasks. Obviously, that’s not sustainable for everyday use yet, but tech cost trends remind me of those gigantic early cell phones or clunky TVs. Before long, companies inevitably find ways to shrink the hardware, lower costs, and scale up availability. There’s also a fascinating dynamic around what we even mean by 𝗔𝗚𝗜. Some experts say we’re here, others say we’re still far off. Either way, I’m thrilled to see the conversation heat up. This progress isn’t just incremental, it points to AI developing the kind of adaptive reasoning we used to think was the sole domain of human intelligence. For people working in tech, or just following it, days like this feel like we’re living through a turning point in history. 

Our first blog post of 2025! 🥳 Daniel Bryant explores "Three Trends to Watch in Platform Engineering for 2025" 🔮 "The platform engineering landscape in 2025 will be shaped by composability, data-driven optimisation, and the transformative power of generative AI. These trends are not just technical shifts—they represent opportunities for organisations to build more effective, developer-friendly platforms that drive business success." https://lnkd.in/emD_jtm6

Missed the action? Don’t worry, we’ve got you covered! In The Rise of Generative AI at the Edge: From Data Centers to Devices webinar, Pete Bernard, Executive Director of the EDGE AI FOUNDATION, joined forces with Daniel Situnayake from Edge Impulse and Marek Poliks from Particle to dive into the future of AI. They unpacked: 👉🏼 The tech driving generative AI at the edge 👉🏼 Game-changing applications across industries 👉🏼 The powerful impact this innovation has on businesses and beyond Curious how generative AI is shaping the edge? Watch the full session now! Wevolver Edge Impulse Particle