Ryan Kahn

At Jellyfish, we’re dedicated to empowering engineering leaders by providing robust tools to measure and communicate the impact of their teams’ work. Today, we’re taking that one step further with the launch of the Jellyfish API. 🎉 The Jellyfish API gives you the flexibility to connect operational metrics, software deliverables, and engineering investment data to the tools and workflows that power your business. Whether it’s centralizing information or reducing context switching, the possibilities are endless. We tested out our brand new API with Amazon Web Services (AWS) Q Business in order to speed up API utilization, and provide on-demand insights that could be requested in various workflows outside the Jellyfish platform. Here's what we learned:  ✅ Guided API Exploration: Amazon Q helped us quickly identify the right API calls and outputs.   ✅ On-Demand Insights: We used Jellyfish data to answer key questions like team performance, project progress, and metrics — all in natural language.   ✅ Limitless Potential: From automating updates to integrating with tools like Slack, the Jellyfish API opens the door to a more seamless engineering workflow. We’re excited to see how our customers will innovate with this API. Got ideas or want to explore? Email us at [email protected]. Let’s build something amazing together!

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At Forge, our mission is crystal clear: helping software companies build thriving ecosystems through plugins. Here’s how we do it: ͐➡ Technical Enablement & Infrastructure: Everything you need to support your ecosystem from libraries, SDKs, plugin hosting and tooling ➡ Ecosystem Seeding: Getting your ecosystem off the ground with early-stage momentum. ➡ Security, Compliance & Governance: Peace of mind for you and your users. Companies like Shopify, Salesforce, Miro, Microsoft, Slack, Zoom, and Atlassian have already set the gold standard. They’ve shown why extensible ecosystems are a modern blueprint for success. Our goal? To bring this capability to every software company—whether you’re a startup or scaling fast. Extensibility isn’t just a buzzword. It’s a growth engine: 🪄 It fuels revenue. 🪄 It builds long-term scalability. 🪄 And most importantly, it empowers your customers with solutions they never imagined possible. 🔥 Forge makes that possible. #plugins #productlaunch #startup #saas #technology #api

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We've been making some cool examples of things that can be built with substrate.run lately. Here's a simple chatbot that can help you cook: https://lnkd.in/eEZm-nRJ If you're working on building a chatbot, take a look and see what it might look like to use Substrate 🧑‍🍳

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Whole lotta AI products and features fall apart once you remember process and intention are infinitely more determinative of success than the output itself

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This is a very exciting effort and I think it has the potential to be a real "game changer" #foundationalmodels #AI #ML #pioneeringtechnology #metaverse

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Exciting times at Zoox: custom robotaxis are finally coming to San Francisco and Las Vegas (according a recent TechCrunch article) https://lnkd.in/dXxku_b7 The ML platform team at Zoox is #hiring. We're expanding and scaling our platform footprint to accelerate ML development velocity and to support large-scale ML workloads. Checkout the job descriptions in the comments section. #Robotaxi #mlinfra #mlplatform #pytorch

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Check out my presentation explaining magic and our new packaging strategy using the conda ecosystem!

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I wish I discovered Mermaid's flowchart language in Notion earlier, this tool is so easy and useful to work with. (https://mermaid.js.org/) For example, a lot of our customers have requested Subscription support in RevOps.io. So we're building a Subscription synchronization feature in RevOps.io that tightly couples Renewal and Expansion updates to a Subscription object. Using Mermaid's flowchart language, I can easily show examples of a Customer Lifecycle and a Subscription object. Anyone else finding this tool to be useful?

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On April 18th, just last week, Meta unveiled Llama 3, lauded as "the most capable openly available LLM to date". This remarkable achievement by the Meta team comes hot on the heels of Llama 2's release last July. Notably, the new models surpass their predecessors and competing offerings from other providers in terms of performance. Meta's commitment to open sourcing these powerful models while prioritizing model safety and responsible usage is commendable. (https://lnkd.in/ghv3RJRz) Yesterday, Microsoft introduced Phi-3 Mini, a member of the Phi-3 family of models, promoted as "the most capable and cost-effective small language models available". According to Microsoft, the key to achieve high performance in such a small package lies in the quality of the training data. The model has been open sourced and is now available on Ollama and Hugging Face. (https://lnkd.in/gKgSmrBn)   These compact yet powerful models serve as invaluable tools for creators eager to bring their visions to life or simply experiment with cutting-edge technology, particularly for those with limited access to resources.   Shortly after the release of Llama 3, reports began surfacing of enthusiasts running the 8B model on a Raspberry Pi 5 equipped with just 8GB of RAM—a modest $80 single-board computer. (https://lnkd.in/gbeQPhQ2) While the performance understandably reflects the limitations of such a platform, the fact that the model runs and generates an output is nothing short of magical. Similarly, the Phi-3 Mini model can run on ubiquitous devices such as smartphones.   Reflecting on my own journey, I recall the pivotal role that early access to a low-cost computer played in shaping my passion for coding. The gift of an 8-bit Commodore 64 home computer ignited my curiosity at a young age. Later, with the guidance of an outstanding Computer Science teaching staff at my high school IISS Marconi-Hack Bari, I embarked on ambitious projects like a networked multiplayer version of Battleship written in Turbo Pascal and 8086 Assembly, complete with custom sprites and lo-res graphics. These formative experiences paved the way for my career, eventually leading me to various engineering and leadership roles.   It all began with a simple, low-cost, modestly capable computer used for experimentation—a gateway to discovering my life's passion.   I encourage educators and parents alike to consider setting up similar low-cost experimentation environments. By introducing younger generations to open-source AI technologies, we can nurture their creativity and help them uncover their true passions. It's not just a weekend project—it's an investment in their future and the future of innovation and discovery. #education #youth #AI #LLM #future #innovation

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This right here. These are the moments you live for as an Engineer. Domo.AI is a game-changer. Our customers are amazed at what they can do. Raw data to critical business insights... in seconds. Bring on the #ai #revolution

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💻 Day 16: Deeper Dive into Streams & File Operations 🔄 Today, I delved deeper into C++ streams and learned how to copy data between files efficiently! 📂✨ Key insights: File Streams (ifstream/ofstream): Essential for reading from and writing to files. Copying Data: Used streams to open, read, and transfer data from one file to another, exploring how std::ios flags like ios::in, ios::out, and ios::trunc work together. Error Handling: Managed file errors, ensuring robust file operations by checking stream states. Learning how to manipulate file streams opens up so many possibilities for data management in programs! 📊 Aman Raj Masai IIT-G x Masai #dailylearning #C++ #FileHandling #CodingJourney #100DaysOfCode #LearningEveryDay

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If you're attending Trustmarque Fusion, come and meet Sumo Logic at this one-of-a-kindI come and meet Sumo Logic at this one of a kind tech and leadership conference and learn how the #poweroflogs can fuel #DevSecOps. 🔥#TMfusion24

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If you are working with Docker... I highly recommend looking at the Slim toolkit. https://lnkd.in/gX_Gb9Kf Why? Slim allows developers to inspect, optimize, and debug their containers using its xray, lint, build, debug, run, images, merge, registry, vulnerability (and other) commands. It simplifies and improves your developer experience building, customizing and using containers. It makes your containers better, smaller and more secure while providing advanced visibility and improved usability working with the original and minified containers. Don't change anything in your container image; minify it by up to 30x to make it secure, too! Optimizing images isn't the only thing it can do, though. It can also help you understand and author better container images. Keep doing what you are doing. No need to change anything. Use the base image you want. Use the package manager you want. Don't worry about hand-optimizing your Dockerfile. You shouldn't have to throw away your tools and your workflow to have small container images. Node.js application images: from ubuntu:14.04 - 432MB => 14MB (minified by 30.85X) from debian:jessie - 406MB => 25.1MB (minified by 16.21X) from node:alpine - 66.7MB => 34.7MB (minified by 1.92X) from node:distroless - 72.7MB => 39.7MB (minified by 1.83X) Go application images: from golang:latest - 700MB => 1.56MB (minified by 448.76X) from ubuntu:14.04 - 531MB => 1.87MB (minified by 284.10X) from golang:alpine - 258MB => 1.56MB (minified by 165.61X) from centos:7 - 615MB => 1.87MB (minified by 329.14X) Rust application images: from rust:1.31 - 2GB => 14MB (minified by 147.16X) Java application images: from ubuntu:14.04 - 743.6 MB => 100.3 MB

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We need some updates to the Turing test to detect AI in the new world order. Proposal: if you can reliably center a div in html you’re definitely not human.

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Unfortunately OpenAI o1 isn't "reasoning" or "thinking" as we humans define it. OpenAI has (intentionally?) muddied the UI/UX waters by introducing verbs like "thinking" / "analysing" etc. to encourage users to anthropomorphize what is going on behind the scenes. o1 is more like iterative prompt generation, and then doing next token prediction for each prompt using an agent. So, yes — it may generate better answers in some contexts, especially the ones where RLHF has been used on its chain-of-though processes (prompt generation), like maths and programming, but its likely to fall into many of the same general traps as next token prediction. The structure and sequence of tokens doesn't *generally* allow you to infer logic. Syntax is not semantics, and the jury is still out on what level of semantic generalisation LLMs can encode, to say nothing of their implementations of algorithms for logical inference and search. #LLM #OpenAI #o1

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Developing software can be complex, and mistakes along the way can cost time, money, and resources. Here are some common pitfalls to watch out for—and how Tempest House ensures you avoid them: 🔹 Lack of Clear Requirements Vague goals lead to scope creep and misaligned results. We work closely with you from the start to define clear, detailed project requirements. 🔹 Poor Project Management Without the right oversight, projects can quickly go off track. At Tempest House, our experienced project managers keep everything running smoothly and on schedule. 🔹 Inadequate Testing Skipping thorough testing can lead to costly bugs down the line. Our rigorous testing process ensures that the final product is stable, secure, and high-quality. 🔹 Failure to Plan for Scaling Software that doesn’t grow with your business will quickly become outdated. We build scalable solutions that adapt to your evolving needs. 🔹 Ignoring User Experience UX Software is only effective if it's user-friendly. Our UX/UI designers craft intuitive interfaces that are as functional as they are beautiful. At Tempest House, we’ve seen—and solved—it all. Don’t fall into these traps; partner with us for flawless software development from start to finish. #SoftwareDevelopment #AvoidPitfalls #TempestHouse #TechSolutions #ProjectManagement #CustomSoftware

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