Peter Yao

Having lived in SF bay area for so long, I came to know the big coffee culture scene here. I was totally consumed by it a while ago and spent years trying to attain the “perfect" latte. I published a fun coffee story and my entire home setup, which took weeks of research and multiple iterations, in my blog link in bio. Meanwhile, to all fellow coffee loving tech peeps, here are some top tips that no one told me. Put it in practice at home or in microkitchens. - A big factor in preparing milk suitable for latte art is pressure of the wand. If this is important to you, you need to get a machine that has a strong enough pressure. - When pulling shots, put in 18g of beans and extract 30g of espresso. - The darker the roast, the coarser the setting should be on the grinder, the lighter the roast, the finer the setting should be. - When adjusting the grind setting, do so while the grinder is working if there are beans in the hopper. Otherwise, a bean can get stuck between the burrrs. - Pulling a shot should take 20-30 sec in time, or based on observation. It should look like caramel going out, not a waterfall. - Eventually work your way to using a bottomless portafilter. It punishes you for all the small imperfections when preparing your coffee puck, like any tilt, and uneven distribution. It does so by spraying the espresso all over the place. The more you can get it to flow uniformly, the better your preparation of espresso, objectively. - Seal your beans in a vacuum, so they don’t go stale. The more stale the beans, the more minor adjustment you need to make to grind finer. - When steaming milk in your pitcher, you can tell if it’s done by holding the pitcher and as soon as the heat becomes unbearable i.e. stings, it’s done. - Taking a latte art course at a local coffee shop was the best boost for me to start nailing latte art.

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A data-driven approach to driving wound healing outcomes Marcella Gomez, University of California, Santa Cruz https://lnkd.in/gAkWZYJT Meet: https://lnkd.in/g4AAWkcK YouTube Stream: https://lnkd.in/gwtqaTmf Talk details: https://lnkd.in/gWn3B3cU Subscribe for talk announcements: https://lnkd.in/g5ciuNuX Abstract: Precision medicine requires an ability to predict the response of an individual to a prescribed treatment regimen a priori. Thus, advancement in the field is challenged by a lack of predictive models and, arguably, a lack of time-series information for a highly dynamic system. Here, we discuss work in wound healing, for accelerating wound closure. We argue that timing of treatments is as critical to consider as the choice of drug or therapy. Due to system size and complexity, data-driven methods need to be explored to develop multi-dimensional quantifiable indicators tracking systemic changes. In this work I discuss how bioelectronic devices enhanced with deep learning can help facilitate real-time sensing and actuation for automated decisions in treatment for wound healing and preliminary work in transcriptomic based classification of wound states. Bio: Marcella M. Gomez is an associate professor at UC Santa Cruz in the department of Applied Mathematics and Associate Dean for Diversity, Equity, and Inclusion for Baskin Engineering. She received her PhD from Caltech in 2015 and a B.S. from UC Berkeley in 2009; both degrees in Mechanical Engineering. Her research interests are in the broad field of bio-control leveraging methods in machine learning and control theory. Applications range from controlling single-cell response to driving complex systems such as wound healing. #modeling #simulation #medicine #healing #trauma #predictivemodeling #datascience #data #woundhealing #biology #bioengineering #systemanalysis #sensing #omics

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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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Interesting article from Bloomberg about life at Google's X in a time of layoffs and cost reduction at https://lnkd.in/gmw3GG7C. X is a component of Alphabet (Google's parent company) that incubates new ideas. They have been responsible for some great successes - getting Waymo and a lot of Google's AI work started - but they've also had projects that didn't survive - like Google's attempt to provide Internet access via weather balloons. When you work at a company that has hundreds of billions of dollars in revenues, it's hard to get a lot of interest in an entirely new business idea that brings in hundreds of millions. If you have a project that improves ads revenue by that amount, or decreases capital expenditures, you can do it, but if you want to, say, build wearable tech, it becomes hard to attract the attention of marketing or product. So, new ideas often die on the vine. For the most part, this is good and proper. Companies may have the financial wherewithal to branch out, but more often than not, they consider it a distraction. And they are probably right - it's hard to argue that Meta was right to divert such a huge chunk of their resources to chase after the metaverse. They've (rightfully) pulled back, and are more focused on their core business again. On the flip side, if you are in the tech sector, and you don't innovate, you are likely to get left behind at some point. So, you need to make and manage these investments somehow. When I joined Google, the CEO had a 70-20-10 rule - 70% of effort went to core businesses, 20% to broader efforts to improve Google, and 10% to stuff that's completely blue-sky. This is probably not completely right, but it is also probably not completely wrong. X is the division of Alphabet that is *specifically* designed to bring blue-sky products to life. Unsurprisingly, they've had to pivot and rethink their strategy many, many times. The article interviews a number of people who have worked at X over the years; it's well worth a perusal, for folks who are interested in the story.

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🚀 Insights from Pathways to Tech Event #16 🚀 I recently had the privilege of attending the Pathways to Tech event, featuring an incredible lineup of industry leaders: Dennis Crowley - Founder of Foursquare ($150M Revenue) Tariq Afaq - First Engineer at AppLovin ($30Bn IPO) Julian Alvarez - Former SWE at Meta, CEO of Wisdolia ($20K+ MRR) Hamza Ali - CEO of Olostep (Hiring Headstarter Fellows) Erik - ML Engineer Intern at TRC, CS Creator with 75K followers Here are some of my key takeaways: 🔹 Dennis Crowley emphasized the power of team collaboration and the importance of creating emotionally connective products. His reflections on the role of software engineers in the AI age and the challenges of building a product with a potential exit in mind were particularly enlightening. 🔹 Julian Alvarez shared his journey from coding as a kid to founding Wisdolia. His advice on minimizing startup mistakes and focusing on specific user groups to drive business growth was truly inspiring. 🔹 Hamza Ali discussed the challenges of fine-tuning AI models and his mission at Olostep. His insights into using AI to enhance user experience were thought-provoking. 🔹 Tariq Afaq and Erik provided valuable perspectives on scaling tech companies and the role of personal motivation and growth in the tech industry. Favorite Speaker: Dennis Crowley’s discussion on the human elements of startups and impostor syndrome was particularly impactful. His focus on maintaining good health and staying updated with new tools resonated deeply with me. If you missed the event, you can catch the full video here: https://lnkd.in/d5-ZYukg Huge thanks to @ Headstarter for organizing this insightful event! 🙌 #TechEvent #PathwaysToTech #Foursquare #AppLovin #Wisdolia #Olostep #AI #Startups #TechIndustry #Headstarter

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Creating a strong GitHub profile with consistent contributions can catch potential employers' eye. However, some may not be aware that you can commit to a GitHub repository with past dates and improve your commit history by simply writing dummy things in a private text file that nobody sees.

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“There’s no jobs for Jr Software Engineers out there!” NOT TRUE…But there are some major issues in today’s hiring market. 1. MISALIGNED FOUNDATIONAL EXPERIENCE: The majority of aspiring SEs are either: Recent CS grads (less hands-on exp); OR, Bootcamp grads (less theory). Meanwhile...Most enterprise companies who hire a ton of SEs are looking for CS grads that ALSO have hands-on experience already. 2. MISALIGNED TECH STACKS: The majority of aspiring SEs are only experienced in NodeJS and/or Python. Meanwhile…Most of the companies who hire a ton of SEs are using Java or C# backends. Companies using NodeJS or Python backends are often smaller and can't hire as many SEs. That’s why our Enterprise Accelerator is making a difference. We identify diverse CS grads who are hungry, and we teach them the hands-on Java skills that companies are using in the real world over 3 months. Best of both worlds 😎 If you're interested in seeing some of this kind of talent--send me a DM and we'll get you connected. Want to join our next Enterprise Accelerator cohort? Stay tuned for the next webinar in early August.

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C++ Next Gen - I recently came across Herb Sutter's latest update on Cpp2 and cppfront. Check it out here: https://lnkd.in/gTabj6sx. I'm excited to see that the C++ next-gen - Cpp2 - is getting evolved. The Cpp2 is a new syntax of C++, which is compiled by cppfront. The compiler builds Cpp2 into standard C++ code. Impressively, C++ and Cpp2 are interoperability i.e. they can be used together like Kotlin and Java, Swift and Object-C. The cppfront promises to be safer and simpler. It introduces interesting features that C++ lacks, such as contracts, metafunctions, and reflection. Here's a snippet in Cpp2: main: () = {    words: std::vector = ( "Alice", "Bob" );    hello( words[0] );    hello( words[1] ); } hello: (msg: std::string_view) =    std::cout << "Hello, (msg)$!\n"; Although it differs from C++ syntax, mastering a new syntax shouldn't take much effort. Looking forward to writing in this new iteration of C++ soon! #cpp #cpp2 #cppfront

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Hey there, Domo users quick update coming your way!  We're super excited to announce this: you can now harness external AI models in Magic ETL. Our new AI Inference tile lets you deploy any of your eligible externally hosted models, like Databricks and Amazon Bedrock, within Magic ETL using Domo’s ML connectors.  (Note that the models will need CSV input and output formats. We plan to expand in the near future to include JSON-based models in the near future.) I'm stoked to share this update, being able to supercharge your ETL with your own model will give you the ability to elevate your data game like never before!  Curious about what this means for you? Dive into all the details right here: https://lnkd.in/gcguUqs6 #domoupdates #domoproduct 

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🍜Anybody up for some ramen? I am excited to share that I am back in the garage, building again (it’s actually a house in the Berkeley Hills). We are taking the wraps off of Supercog AI, a new startup focused on solving Application Integration using LLM powered agents. My co-founder in this new venture is a great friend of mine (and a former co-founder partner), Alex Osborne. Alex and I have worked around the application integration space for a long time, and we are unrealistically excited about applying the GenAI stack to this problem. Not many people relish the task to get some bits to move from system A to system B. But it’s a critical job to be done, and that’s led to a lot of brittle scripts, a myriad of inflexible “no code” tools, and a lot of hand crafted SQL. But the power of the Large Language Model, trained on a huge corpus of information, offers a remarkable tool to solve this problem. The LLM you use today already knows the APIs of hundreds of popular systems. It knows the SQL dialects of every major database. It understands the semantics and data schemas of many popular SaaS systems. It understands much of the specific domain in which your business operates. I like to call the AI revolution “the last platform shift”. That may turn out to be hyperbole, but I definitely believe we are in the very early stages of seeing what this new stack can enable. I know we are hardly the first folks to claim that “amazing stuff is coming!”. But this is why Alex and I have decided to focus on a real and hard problem. If we can prove that LLMs can power a new way to solve this problem, it will be the first successful *new* approach in 15 years.. We will have much more to share about this new platform soon. In the meantime, if you’re interested in getting a peek - or even better if you have application or data integration tasks that you would like some help with - please reach out because we want to help. #genai #startups #backinthegarage

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This is a question many Data Engineers asked me: How are systems like Apache Druid, Apache Pinot, Clickhouse, etc... different from RisingWave? Aren't they all "real-time" and can't they do "streaming"? There are indeed fundamental differences between these systems and RisingWave. For OLAP Databases, their computation model is still executing in batch. They are "real-time" in a sense that their adhoc queries can execute really quickly. And they can do "streaming" in terms of ingestion, they can quickly stream in records, and run batch computation on them. For RisingWave, it's differentiated, because it does incremental rather than batch computation instead. So we can achieve lower latencies for streaming queries, and spend less compute to get the same results. That being said, streaming systems do not entirely replace OLAP/OLTP systems as well, there are many use cases where both can complement each nicely. Catch the talk to understand more about the fundamental differences, and how these systems can work cohesively. #risingwave #olap #streaming #database #realtime

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I'm reaching out to my LinkedIn community during a time of unexpected change. Recently, I found myself among the many affected by Tesla layoffs. After 16 months of pouring my passion and skills into projects I truly believed in, saying goodbye was not easy. During my tenure on the Vision Automation team, I had the privilege of: * Enhancing vehicle quality by using computer vision to identify defects. * Architecting an in-house machine learning platform for efficient model labelling, training, and deployment. * Developing a robust labeling platform to gather SME insights and train cutting-edge ML models. * Streamlining our authentication processes by transitioning to Microsoft OIDC. * Creating an application alert system by customizing Prometheus, Grafana, and Alert Manager for application-specific alarms. * Collaborating with an extraordinary team of engineers who inspired me every single day. Now, as I navigate this transition on a visa with a tight 60-day timeline, I am actively seeking opportunities where I can bring my expertise to the table. I'm looking for roles in Software Engineering, Distributed Systems, or Machine Learning Operations where I can continue to grow and make an impact. If you, or someone you know, can guide me towards potential opportunities, I would be grateful for your support. Let's connect and explore how my experience can benefit your team. Together, we can achieve great things! #TeslaLayoffs #OpenToWork #Tesla #EngineeringExcellence #MachineLearning #SoftwareEngineering

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We released a new update of our Visual Studio Code Java extension. Go try it! Bunch of new improvements and already supporting JDK 23 Early Access builds as the extension is directly leveraging javac. https://lnkd.in/g8BKsNjS #java #IDE #OpenJDK #VSCode

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"Females can act like glue within a team, contributing to the overall success the same as men, while injecting a different perspective." - Jian Cheng, Senior Full Stack Developer at Edge Signal. We had the pleasure of speaking with Jian and other female leaders within our ecosystem in celebration of #IWD2024. With 15+ years of software programming experience, Jian is in a unique situation – being a senior developer, female, Chinese, an immigrant, and currently the only female on a small start-up team that is tasked to build an AI-powered edge computing platform, Edge Signal. Read the article to learn more: https://lnkd.in/eUyBJrVg. #tech #femalesintech #womenintech #edgesignal

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Perfection is an illusion; start, stumble, and learn. Mistakes are the stepping stones to mastery.

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Check out the "Titan Text Premier Demo" built by my team on this page

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