Jen Granito

How do you build for Gen Z? 🏃‍♂️ Immediacy 🎨 Flexibility 👀 Authenticity These are the principles you need to ground your product in. Gen Z are the first digitally native generation. They've grown up in a world of hyper-connectivity, hyper-stimulation, and hyper-personalization. One where everything not only auto-saves and auto-updates, but auto-optimizes too. And while they trust in technology to anticipate their needs, they're much less trusting of the platforms where they spend their time. So what does this mean for how you build, hire, and market? Excited to share my #Config2024 talk, where I explored exactly this 👇 Grateful to the folks whose stories added to these insights: Yuhki Yamashita, Dabney Dayes, Adam Polselli, Peter Yang, Helena Jaramillo, Ceci Mourkogiannis, David Hoang, Colin Dunn, Andy Chung Figma 🙌 Most of all, thanks to my Gen Z co-creator, Maddie Johnston, for pairing with me to bring this to life 🙏 https://lnkd.in/gx833AuF

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I had such a great time chatting with Lenny Rachitsky in this week's podcast! We talked about some of the lessons I've learned over my career, like getting my hands deep into execution, using storytelling and metaphors to build stronger products, and leading with curiosity so I can constantly learn from everyone (and, as a side benefit, stay focused in meetings 😀 !). So many of these tactics I've learned from the brilliant and generous people I've been surrounded by throughout my career -- thank you all! And of course, you can find more about these lessons in my "Hard Parts of Growth" series about product, leadership, and scaling, at amivora.substack.com.

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🧠🧠🧠 Let's not forget that daily model updates does not mean marketers need to leverage their MMM every single day. It means that our data is ready when YOU need it, not when we feel like running the model. Does that cost more for us? Sure it does. But maybe doing things just a bit differently is what our industry needs. Reach out if you have questions 🤙🏼

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I'm finally ready to share an experiment I've been working on with the Future Audiences team at Wikimedia. It's a pretty special team where I get to have space to think about the intersection of things like LLMs and the evolving online space of (mis/dis)information: specifically how can this technology not replace humans as an information source, but help better connect us to living sources of information created by humans. I have this hope/dream that tools for us to verify information in a world where creating questionable information is so widespread will be as easy and normal as your internet browser coming with built-in adblockers to protect you from being overwhelmed with pop-up window spam. Anyway, the experiment we have is called Citation Needed, and if you are using the Chrome browser, I'd love for you to try it out. After you install it, you can use it to check short texts online to see if they are corroborated by information on Wikipedia, and have the opportunity to learn more about it. It's still experimental, and uses LLMs/AI, so you might see some funny behavior once in a while -- which you can report to us in the extension -- though I invite you to imagine what this functionality could look like in the near future, and/or beyond the confines of a browser extension. And then let us know where this sci fi daydream takes you. Link: https://lnkd.in/eQwd4iqK

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Today at #GoogleIO we shared lots of exciting news about how the team is working to reimagine Android with AI at its core. From updates to Circle to Search, additions to Gemini on Android and the announcement of Gemini Nano with Multimodality, it was truly incredible to see AI on Android take center stage at Shoreline. In case you missed it, check out the recap below! #GoogleIO #Android #CircletoSearch #Google

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Ever wondered how to get started with Heroku? Join us on Thursday may 9th at 10:30 PDT to learn how to launch your first app!

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For the past 4 years at Tecton, I've worked with some crazy talented coworkers and customers to build a product that can help companies like Roblox, FanDuel, Hello Fresh, Flo, and Atlassian put AI systems into production. Something that's always been notoriously hard for teams to pull off. For a while though Tecton was hard to get your hands on, requiring conversations with our sales team and heavy-weight infrastructure like Spark. In this last year, that all changed. We rebuilt Tecton on top of a Python-native compute engine we called Rift, meaning that now anyone with Python and some data can put an AI system in production. And last week we took things a step further and made it so anyone can sign up to explore the product (https://lnkd.in/gRyV-emS). You can even run the whole thing with zero setup in a Colab notebook (https://lnkd.in/g_erUX8Y). Getting here feels like a big personal milestone. After a decade of working on ML platforms, anyone in the world can finally try the product I've helped build. Give it a whirl. Let me know what you think. And stay tuned for more cool updates!

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How do you combat zoom anxiety? Share your tips below!

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Tinkering fuels innovation and curiosity. It allows us to truly understand the tools and systems we work with at a granular level. Recently, I've been tinkering with Rust, a language gaining popularity for building reliable, safe, and sustainable systems at scale. The best way to learn is by doing. So, I turned our simple summarization proof of concept, Distill, into a CLI leveraging Rust's performance and memory safety advantages. As builders, it's our responsibility to continuously look for optimizations in everything we do. To ask questions and challenge the status quo. To learn and be curious. I encourage you to give Distill CLI a try, tinker with it, and share your feedback. And as always – now, go build! #AWS #tinkering https://lnkd.in/e7HUQwEt

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"Since 2018, we have increasingly leveraged Rust for critical workloads across various [AWS] services like S3, EC2, DynamoDB, Lambda, Fargate, and Nitro, especially in scenarios where hardware costs are expected to dominate over time." We've seen a lot of success with Rust at AWS, including our work on Firecracker, on Lambda's container dataplane, and on many other systems we've built. I love the fact that we can get memory safety without compromising performance or efficiency. I also enjoy seeing how much less time my teams spend tuning runtimes or debugging memory issues. I also really appreciate this sentiment from Werner's post: "... this is not a call to rewrite everything in Rust. ... It’s about using the right tool for the right job. This means questioning the status quo, and continuously looking for ways to incrementally optimize your systems – to tinker with things and measure what happens." Make decisions about programming languages the same way you make all critical engineering decisions: with data!

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Here's the problem with AI overviews. Regular AI is just predicting the next word so you can see how it goes to the riddle and gets this wrong. RAG AI is supposed to ground this by summarizing search results, but the search results are so broad and generic right now that those too misunderstand the query and go right to the popular riddle - and you get a crap answer. This is over exaggerated by my example, but it holds true for all complex non-trivial queries.

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Last week, in the 100+ years’ old Palace of Fine Arts, gorgeous in the early summer California sun, over 30,000 people and some robots showed up for the GenAI summit https://genaisummit.ai/#/. The somewhat disorganized conference that attracted attendees from all over the world is a testimony of the current state of AI: everyone wants to get in, a LOT is happening, no one really has the paved path, but there is no doubt the future is here. As a student of AI, my key takeaways: ▶ Development of base models will be done by a few players who have the money to burn. One presenter quoted up to $100M for a single model. Though the architecture of the base models may be similar, each player has their secret sauce. And the winner of one model is unlikely to take all. All players are rapidly developing and revolutionizing. 🔹 Model “aggregators” fit domain-specific data to base models. They are not “picky” about which model to use. They add value by fine-tuning the models for specific domains. From prompt engineering to RAG to fine-tuning, SMEs play a key role in “landing” LLMs well. There is a boom of startups in this space. ⬆ Data is still foundational. It’s the era of unstructured data. New data storage and processing technologies are the backbone. Is there “enough” data for AI? It depends. Synthetic data is widely used. While “connected” data on the web is relatively easy for the models to access, “protected” data in enterprises requires jumping many hoops, including expert domain knowledge, governance and “imagining” the business problems they can solve. Data about the real world is fast growing, collected from sensors and fed into robotics. 💲 GPUs are expensive and power hungry. Optimization is the path today. Alternative hardware can take time. The bigness of AI meets the smallness of nuclear power. Mini nuclear power plant https://lnkd.in/giJkjTiG. 🛠 While the base model developers are relatively a small elite group, often with deep academia roots, applying the models to real world problems needs everyone in their current job working with AI. AI certainly created new job titles, but also makes it increasingly easier for the public to use it as a new “tool”, instead of a complete career change. 🐬 The most optimistic prediction of AGI is 3 years. The honest answer is no one really knows. How far will AI go from data, information, knowledge, intelligence to wisdom? Opinions differ. When the answer is 42, how would we know 😉 ? 

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Please Google do better. Google, you may be a technology company, but you claim to serve 'the people'. So why is it that you hide behind your technology and algorithms when instead you could be being a conduit between your technology and the people? As some will already know Google Search did a whole lot of website deindexing in February 2024. Google announcements at that time indicated that the then algorithm update would take time to settle and that no-one should be alarmed (by outlandish swings in search results analytics). Unfortunately we really only understood the magnitude of things in March https://lnkd.in/eHnMBWZg ... still without the company giving their citizens a briefing. Instead we've had poorly prepared employees fail to answer questions in webinars, conference panels and interviews about the matter. (I suppose there are some people who are irreplaceable - thank you Matt Cutts for your years of service) As the manager of many websites (on behalf of clients) we have been in utter dismay since late February when a number of websites suddenly started unexpectedly loosing traffic (and now more recently Domain Authority). Personally, I can't imagine that the websites for a local dentist, a cookie maker or a blog about transporting cars in Australia would be offenders of some sort of "perception" change. The arguments that there are technical issues or AI content issues with any of these websites (they don't even have ads on them!) just doesn't stack up ... and yet these websites have on average lost 60% of the traffic they achieved at the same time last year. We have worked furiously at all sorts of SEO strategies (adding even more human written copy, inserting business specific photos, adding schema markup, reviewing all technical aspects of the website, caching, hosting ... you name it) in an attempt to halt the dramatic decline in traffic volumes, with nothing being evident in Webmaster Tools that there's even been any type of problem with these websites. Without knowing if deindexing might have occurred (despite watching as fewer and fewer pages for these websites appear in SERPs) and no actual singular explanation from Google; these websites have 'died'. Even the tools for tracking these sorts of things provided by Google have "played dumb" and been non-responsive to our earnest efforts to preserve these websites to this point. From the difficult to configure and increasingly problematic GA4 reporting to the invasive "helpful?" password capturing nature of Google Chrome and the outright annoying ads on pause over on YouTube. It feels like in 2023 the corporate beast that is today's Google stepped over some invisible boundary ... I don't like. https://lnkd.in/eu22bWpE

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Ever wonder how teams at Airbnb & directors like Spielberg turn big ideas into unforgettable experiences? ✨ It all starts with storyboarding - it’s like sketching out your project with a comic strip to visualize each step before you begin. We’re launching a "Multimodal Storyboarding Starter Kit" for developers, enabling you to unlock GenAI storyboarding in your apps. Check out StoryFlow, a demo app built on VideoDB: 1. Enter your app description. 2. List user steps. 3. Hit Generate & watch your user journey come to life! Want early access? Reply or like this post! :)

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In February, we announced the launch of Rufus, Amazon’s generative AI-powered shopping assistant, to a small subset of customers. Last week, we shared that Rufus is available to all U.S. customers in the Amazon Shopping app, and today we are sharing that millions of customers used Rufus to help them shop Amazon’s wide selection quickly and easily this Prime Day.   We built Rufus to help customers make more informed shopping decisions, and we’ve been thrilled to hear they are using it to understand product details (“Is this coffee maker easy to clean and maintain?”), find deals (“What are deals on microwave ovens?”), get product recommendations (“What are the best lawn games for kids birthday parties?”), compare products (“Compare OLED and QLED TVs”), and more. In fact, customers have asked Rufus tens of millions of questions so far, and counting.   It’s still early days for Rufus and generative AI, but we’re excited for what the future holds, and look forward to hearing more from customers about how they are using Rufus to find what they want and need in Amazon’s store. https://lnkd.in/gpY4WQYJ

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Protecting users and developers on #GooglePlay is paramount and ever-evolving. Proud to share that as a result of our hard work in 2023 alone we: - Prevented 2.28 million policy-violating apps from being published thanks to our investment in new and improved security features, policy updates, and advanced machine learning and app review processes - Identified bad actors and fraud rings more effectively and banned 333K bad accounts from Play for violations like confirmed malware and repeated severe policy violations - Rejected or remediated almost 200K app submissions to ensure proper use of sensitive permissions such as background location or SMS access Our teams are constantly working together on new ways to protect your experience on Google Play and across the entire #Android ecosystem. Read more about how we help keep you safe: https://lnkd.in/gUT4grua

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