Eason Tianyi Zhang

🎉 Big congratulations to our incredible team (Haoyu Chen, Nick Greenquist,Yuxing Wang, Sridevi Maharaj, Ruiyang Wu and many more) for delivering several quarters-long impactful features on the Play Store! 🚀 We’re thrilled to have launched key updates like Search Home, Sports Moment, and WearOS recommendations, all designed to enhance personalization and help billions of users worldwide search and discover content they love. 🌍✨ Check out the Play Store Q3 updates: https://lnkd.in/dn5wx8Mi #GooglePlay #Personalization #Recommendation

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Come join us tomorrow in SF to learn more about the latest updates to run AI workloads on Google Cloud!

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I recently had the opportunity to attend 3 major AI events in the last 30 days, where I gained valuable insights into the future of artificial intelligence. Here are some key takeaways: Amazon AI Day: - Amazon CTO (Werner Vogels) highlighted the potential of generative AI and large language models in driving innovation and societal impact, particularly in healthcare and sustainability. - Explored how generative AI is revolutionizing development processes and transforming businesses across industries. MagicBall - AI Week: - Showcased advancements in AI infrastructure by over 24 startups from Bengaluru, emphasizing the city's significance in AI development. - Engaged in discussions on responsible AI development and ethical considerations for the future. Microsoft AI Day: - Microsoft's Innovation Hub India CTO (Sandeep Alur) discussed AI's critical role in digital transformation and the company's commitment to ethical AI development. - Showcased the revolutionary potential of Generative AI and its integration into Microsoft Azure. These events, combined with insights from the ISB CTO program, emphasize that AI is here to create new opportunities and possibilities, not to take away jobs. Embracing a growth mindset is crucial to thrive in the evolving AI landscape. The AI revolution has just begun, and it's essential to adapt and innovate for a sustainable future. #GenAI #AI #BrightFuture

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How you can make your LLM applications better!

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In this episode, we discuss Learning Task Decomposition to Assist Humans in Competitive Programming by Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang. The paper presents a method to enhance human understanding and repair of language model (LM)-generated solutions by automatically breaking down complex solutions into simpler subtasks. They introduce a novel objective called assistive value (AssistV) to measure how easily humans can repair these subtasks and validate their method through a dataset of human repair experiences. The approach significantly improves the problem-solving ability and speed of non-experts in competitive programming, allowing them to solve more problems and match the performance of unassisted experts.

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Three insights from the TEDAI San Francisco X Factory X AI at Meta CodeGen Hackathon. Had the pleasure of judging a fantastic hackathon in SF yesterday. Here's the biggest things I took away from iteration on the cutting edge of GenAI for code: 1) 𝙂𝙚𝙣𝘼𝙄 𝙘𝙤𝙙𝙞𝙣𝙜 𝙨𝙩𝙖𝙧𝙩𝙚𝙙 𝙬𝙞𝙩𝙝 𝙖𝙘𝙩𝙞𝙫𝙚𝙡𝙮 𝙖𝙨𝙨𝙞𝙨𝙩𝙞𝙣𝙜 𝙙𝙚𝙫𝙨 𝙖𝙩 𝚠̲𝚛̲𝚒̲𝚝̲𝚎̲ 𝙩𝙞𝙢𝙚, 𝙗𝙪𝙩 𝙂𝙚𝙣𝘼𝙄 𝙖𝙜𝙚𝙣𝙩𝙨 𝙣𝙖𝙩𝙪𝙧𝙖𝙡𝙡𝙮 𝙛𝙞𝙩 𝙖𝙩 𝙙𝙞𝙛𝙛 𝚛̲𝚎̲𝚟̲𝚒̲𝚎̲𝚠̲ 𝙩𝙞𝙢𝙚. Iterative agenic workflows can run at review with automated vetting of generations, and only serve edit suggestions shown to improve a tested outcome (i.e. memory efficiency). Bonus is that this can scale with inference time compute to try more or less variations or revision cycles. 2) '𝘾𝙤𝙙𝙚' 𝙖𝙨 𝙖𝙣 𝙖𝙗𝙨𝙩𝙧𝙖𝙘𝙩 𝙘𝙤𝙣𝙘𝙚𝙥𝙩 𝙤𝙥𝙚𝙣𝙨 𝙖 𝙬𝙤𝙧𝙡𝙙 𝙤𝙛 𝙥𝙤𝙨𝙨𝙞𝙗𝙞𝙡𝙞𝙩𝙞𝙚𝙨 𝙛𝙤𝙧 𝙣𝙤𝙣-𝙨𝙤𝙛𝙩𝙬𝙖𝙧𝙚-𝙙𝙚𝙫 𝙚𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜 𝙙𝙞𝙨𝙘𝙞𝙥𝙡𝙞𝙣𝙚𝙨. Many tools in these areas involve cumbersome UI's that ultimately translate points and clicks into complex config files, and LLM's are pretty good at editing these underlying files directly. 3) 𝘾𝙤𝙙𝙞𝙣𝙜 𝙖𝙗𝙞𝙡𝙞𝙩𝙞𝙚𝙨 𝙞𝙣 𝙢𝙤𝙙𝙚𝙡𝙨 𝙖𝙧𝙚 𝙜𝙚𝙩𝙩𝙞𝙣𝙜 𝙢𝙤𝙧𝙚 𝙘𝙤𝙢𝙥𝙖𝙘𝙩 𝙩𝙝𝙖𝙣 𝙚𝙫𝙚𝙧. One hackathon team was able to use a combination of synthetic data creation/refinement and model distillation (in this case from my near and dear Llama 405B) to fit highly advanced code translation ability in a 14B model. I have a feeling this trend will continue, which will open up more inference compute heavy coding opportunities like broad repo summarization. Bonus here - the resulting model was open sourced by Jason Lu: https://lnkd.in/gswMbCR3 Shout out to SHACK15 and Cerebral Valley for hosting. Incredible views and vibes.

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A few months ago, I had the honour to be a guest on Qingyue(Annie) Wang https://www.thriveup.co/ podcast which focused on stories about my career pivot from microbiology to software engineering. I shared my somewhat mundane journey not knowing the profound impact it would have. To my surprise, during a coffee meetup, several people approached me to express how much my story inspired them. This was a humbling reminder of the power of sharing our paths regardless of how little we think of it. I had an idea to start podcasting, but I didn't know how or what to talk about. Until I met Fauwial Khan on a tech event who also had a dream of starting his own podcast. After a few intense brainstorming session on podcasting topics. Suddenly, everything clicked. We decided to create a platform to bring people together through their stories. That’s how Vancity Podcast https://lnkd.in/gxvdnnSH was born. Our first episode? Recorded with just a $12 Amazon earbud (we have proof!). Agile podcast development, right? Ship fast, get feedback and iterate. It's fascinating how two novices in podcasting were able to join forces and launch a podcast channel. What really propelled us was our shared vision and the small, incremental steps we took to achieve our goals. Upon hearing about our project, numerous individuals generously offered their expertise in storytelling, podcast setup, and interviewing techniques. I am deeply grateful to be surrounded by such kind-hearted and altruistic individuals. None of this would have been possible without their invaluable support. If you are interested to listen to stories told on Vancity live podcast, follow us on https://lnkd.in/gxvdnnSH. You know what's even better? share your stories on Vancity live podcast! Reach out to either Fauwial Khan or myself. #Podcasting #VancityPodcast #Storytelling #CommunityBuilding

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Watching Professor Girotra talk about recent developments in Chinese companies using GenAI and putting that in perspective with what we learn from Western companies, it’s exciting to see the technology’s potential being explored from different angles. Take a look at Kling, the GenAI tool that Kuaishou (a company comparable to TikTok) built to allow its users to generate videos up to two minutes long with a resolution of 1080p / 30 fps. This video is from a prompt: ‘A giant panda is playing guitar by the lake.’ Girotra's video - https://lnkd.in/gfanV4Xk. He's also the author of the Generative AI for Productivity certificate program published by eCornell. #IWork4Dell #GenAI

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Getting started with AI can seem daunting, especially when contemplating its safety against data privacy. But past that fear lies a fix for itself: AI tools can be harnessed to overcome cybersecurity hurdles. Join us for an insightful discussion at the intersection of security, building resilience, and emerging technologies like AI, IoT, and others such as operational technology, and products intersecting with information technology and engineering. Get inspired, learn something new, and connect with peers, partners, and Googlers!

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Today I'm sharing this 🔥 video from our recent Engineering onsite at Demandbase HQ in SF! https://lnkd.in/eFAFR6QG We were so fortunate to host Zhengxuan Wu and Aryaman Arora, two upcoming AI researchers from Stanford University Department of Computer Science. Their approach to fine tuning, called ReFT, targets the representations emitted by neural net layers rather than the weights of the layers themselves. This makes it very flexible when using the same base model for swapping multiple fine tunes. The memory overhead is also very low for their intervention weights. Another highlight is how powerful it can be. One POC they showed forced the LLM to speak in only emojis exhibiting ReFT's power to control output. Control is crucial when, for example, you want to prevent your bot from offering customers unauthorized refunds!! If you're already familiar with LoRA, it should be pretty simple to use with only a few extra hyperparameters -- details in the video. Here's a link to the repo. Give them a star! https://lnkd.in/eJScNbzK Thanks again for letting us host your first external talk Aryaman and Zen. It's very exciting tech!!

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Xian Ke, this is incredible! The speed at which you and Vishal Punjabi leveraged crewAI, Streamlit, and various LLM models to create Finbot, a powerful company analysis tool for investors, was mind-blowing. ICYMI, Finbot is here: https://lnkd.in/eSQD69qA I couldn't help but chuckle when I saw the Finbot name - it reminded me of the Wall Street Bets crowd. Maybe you can get them to yolo their life savings based on Finbot's analysis? (Kidding, of course. Or am I? 💎🙌) But in all seriousness, your enthusiasm and passion for AI and LLMs is contagious. It's engineers like you who are pushing the boundaries of what's possible with AI and paving the way for a brighter future.🏆 I'd love to extend an invitation to any other software engineers from the bootcamp to join our Devs Do AI Discord server. It's a great place for engineers without an ML / AI background to connect with like-minded devs, share knowledge, and collaborate on LLM projects. DM me for the invite link. 🤝

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https://lnkd.in/gxJWb4hA Just testing! :) I "wrote" this short article with help of AI - in minutes, but it is about an important difference, that I would like to highlight, between both awesome APAC hubs: HK and SG. For example it would be great if HK introduces LTVP visa for non-immediate family members and it would be also great if SG allows spouses to take up jobs again. The issue is complex, but worth a read!

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Congrats the team on ICML acceptance of the Wukong paper: https://lnkd.in/g-MyahNH, which represents a breakthrough of recommendation model design and efficiency. Recommendation models traditionally suffer from not able to utilize the full computational power of GPU (only 5-10% of peak GPU FLOPS while LLMs can reach >50%), due to their sparsity. Wukong is first of its kind by pushing toward 40% GPU peak FLOPS though model-infra codesign. One of my teams consisting of GPU experts is building a high performance model component libary where we’ll provide highly optimized model components (eg sequence summarization, x-sequence interaction, x-GPU layout scheme) that could be composed - with the goal that models built from this library have high performance out of box to scale the model-infra codesign effort. We are also scaling training beyond the limits that are typical of recommendation models - from hundreds of GPUs to 10s of thousands. If this is the kind of work that excites you, come join us!

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For the first time I am happy about certificate which I received today that remind me the new learning, foundation for next year, and the hours I spent over the weekend for the 10 weeks. Little bit about course: NLP with deep learning The best part is the hands on exercises where we learn the foundations of deep learning, neural networks and the NLP. But it will be useful as a starting point and set the direction in that path.

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Want a preview of what I'm going to be talking about in my keynote for RubyConf? You can catch a glimpse of it here!

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Recently, there has been much discussion about Nvidia's CEO's approach of not having 1:1 meetings while leading 60 direct reports, emphasizing the benefits of a flat organizational structure and portraying 1:1s as unnecessary. Like with many trends, the focus has been primarily on these two aspects. Leaders have attempted to replicate this model by increasing the number of direct reports per manager or even eliminating 1:1s altogether. It's refreshing to learn about another side of the story that many are trying to emulate, one where valuing employees and placing them at the center of the organization is crucial for the company's success.

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Ever wonder what became of encoder-decoder and encoder only models? You will have to wonder no longer, Yi Tay has you covered with an LLM history lesson. https://lnkd.in/eyxh-mKw Great read!

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It’s time for Social Saturday #1 (Stories Beyond Achievements) 🌟 Meet Diksha Gohlyan, a Senior Software Engineer at NVIDIA and Technical Interview Coach at Interview Kickstart, and a former software engineer at Google. 🌟 What inspired you to pursue a career in tech? -> I always wanted to be an engineer growing up, the definition of engineering being building homes. As I grew older, software engineering became a luring field and my interest in computers and exposure to its power led me to pursuing a career in tech. 🤔 How would you describe a typical day at your job? -> A typical day for me would be a few meetings with my team and other stakeholders, a lot of hands-on programming solving problems and resolving bugs, and great discussions with teammates over lunch on any topic really. 🚀 What did you want to be when you were a kid? -> Engineer - Not sure if it was my parents who instilled that on me or the ambition in me wanted to do something different compared to what my family did, but I was clear I wanted to be an engineer, what kind, still unsure. 🌈 Share your favorite childhood memory.  -> This aces all the fun I had with my siblings. We were throwing balloons from our terrace during Holi, and it hit an aunty. She was furious and started ascending up the stairs. My sisters, who were older, jumped over the fence to the other side to hide, but I couldn’t reach and had nowhere to go but to descend down the stairs. The lady caught me and thrashed me. Even with the thrashing its still my favorite moment because it reminds me of all the fun we used to do as kids. 🤔 Your friends describe you as…  -> Hard working, always in a hurry, and sometimes helpful. 🕰️ Describe yourself when you were 22 years old. 🏆 An accomplishment you're particularly proud of? 😓 Reflect on a moment or time when you felt like you were struggling a lot.  🎓 What's the biggest lesson you've learned in your career so far?  ⚖️ How do you balance work and personal life?  🎲 A random fact about yourself. 🎬 What is your favorite movie or series of all time? 💬 A favorite quote or mantra that guides you in your career.  💼 What non-technical skills do you believe are crucial for success in tech? 🚀 A message to young people looking to pursue their career in tech.      Edit: Swipe through the images below to find out more! 👇📸 🙌 A shoutout to your mentor during your early career.  -> Devesh - My ex-manager from Google - I am still in touch with him. Connect with Diksha di by expressing what inspired you most about her journey. And if you're eager for more stories, stay connected! Sharing experiences is how we all grow! 🌟 #YourNewConnection #SocialSaturday #StoriesBeyondAccomplishments #TechInNepal #TechInspiration #NepaleseInTech #WomenInTech

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To smooth your reading experience, let me give a bit of background; I am planning to write tech posts here (irregularly), to share the AI/ML/tech exp between all of us. I came from Hong Kong, where I wrote more on political / cultural, or even dining / winery matters, because that was our major concern, and I would not receive any feedback on any of my tech posts anyway.... but here in North America things are different. I joined some IT Whatsapp groups and the suggestions to problems had been really inspiring. When the democracy foundation is strong, and when the basic ethics are there, we can focus on the state-of-the-art tech, which hopefully can change our lives for the better. So in the next or coming posts, I would formulate some objectives or problems, which I may have a suggested approach solution, but I would like some of you to share your thoughts. It's just like beer talk. I am expecting your words in my coming posts!!

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