Taylor Lehman

Implement super-fast RAG using LlamaIndex Workflows and Groq 🚀 Learn how to build a powerful Retrieval-Augmented Generation system with our Workflows feature, including a comparison to alternatives like LangGraph: ➡️ Create an event-driven architecture for complex AI applications ➡️ Integrate Groq's high-performance LLMs for reranking and response synthesis ➡️ Visualize your workflow for better understanding and debugging Step-by-step guide covers: • Data indexing and retrieval • LLM-based reranking • Response synthesis using CompactAndRefine Read the full tutorial: https://lnkd.in/gRwy4eZ9

32

1 Comment

Recently, I had an intriguing task: I saw my wife enter our daughter's play rehearsal schedule in the calendar manually. I decided to see if I could use LLMs to take events from a detailed rehearsal schedule in PDF format and extract calendar events for my daughter’s rehearsals. This was more than a simple extraction - it had to be personalized - it required understanding nuanced details like recognizing that “full cast” events should include her (LLMs initially missed that), roles she was playing, conflicts etc. I tested several AI tools, including GPT-4o, Gemini, and Claude 3.5 Sonnet. While the initial data extraction had its hiccups (it took multiple passes to get all the events) - I was a bit surprised by that, the real magic came in what these tools could do once the data was extracted: • I got close to 40 events for 2 weeks, then I asked the events on the same day to be grouped together. It was very impressive - it not only grouped but embedded the event details that were grouped into the description. • Renaming the events to improve clarity and context was just a simple prompt. • Finally automatically generating an .ics file with ready-to-import calendar events. This process highlighted how AI’s strength often isn’t just in extracting data but in post-processing it into actionable, user-friendly outputs. In this experiment Claude 3.5 Sonnet performed the best. The key insight? AI tools require thoughtful guidance and iteration, especially when personalizing outcomes - this needs domain expertise. As a tech leader, this reinforced the importance of adaptability—not just evaluating tools for accuracy but leveraging their transformative potential. What are some of your favorite use cases for AI in streamlining everyday workflows? #AI #Productivity #Leadership #TechInnovation

93

14 Comments

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!

39

4 Comments

𝗟𝗲𝘀𝘀𝗼𝗻𝘀 𝗳𝗿𝗼𝗺 𝗦𝘁𝗲𝘃𝗲 𝗝𝗼𝗯𝘀: 𝗧𝗵𝗲 𝗣𝗼𝘄𝗲𝗿 𝗼𝗳 𝗗𝗲𝘁𝗮𝗶𝗹𝘀 𝗮𝗻𝗱 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲𝘀  The 𝘚𝘵𝘦𝘷𝘦 𝘑𝘰𝘣𝘴 biography by Walter Isaacson highlights how transformative a dedication to detail can be in building iconic products. Jobs was relentless about the small things – the often-overlooked details he believed were essential to a product’s soul. Take, for instance, his insistence on a slot-loading CD/DVD drive for the iMac instead of the traditional tray. For Jobs, this wasn’t just an aesthetic choice but a statement of simplicity and elegance. He felt users would sense this refinement, even unconsciously. It’s a reminder that what might seem minor can ultimately shape a product’s perception and feel. This meticulous attention extended across everything Apple created. Jobs was known to care about typefaces, button layouts, and even the arrangement of circuit boards inside devices, setting a standard that every touchpoint should be crafted with care and intention. In software, he pushed for fluid animations and subtle sounds that felt intuitive, creating harmony between user and product. But his focus wasn’t only on the details – he believed in building fully integrated experiences. Apple’s software ecosystem is a perfect example. Consider how iMessage, FaceTime, and AirDrop work seamlessly across devices. This seamless integration wasn’t accidental; it was a result of careful planning where every piece was designed to complement the others, allowing users to switch effortlessly between devices. Another example is iCloud, which connects photos, documents, and apps across devices in real-time, giving users a sense of continuity and connection. For software and digital products, these principles are powerful. Imagine creating an experience that doesn’t just optimize each part but feels unified end-to-end. Integrating design and functionality seamlessly – from backend processes to front-end interfaces and customer support – can turn a functional product into a memorable one. And paying close attention to the details, like smooth transitions or well-paced loading speeds, often makes the difference between a good experience and a great one. Jobs’ approach reminds us that a product’s magic often lies in the fine details and the effort to build an experience that feels complete, connected, and crafted with intention. #ProductDesign #CraftingExperiences #LeadershipLessons

4

2 Comments

Stay ahead of the competition with an AI center of excellence. Learn how to gain the right #AI resources, skills, and strategies: https://lnkd.in/eArUqqgd

4

Apple’s shift away from the annual release cycle toward multiple, smaller launches throughout the year feels long overdue—especially in today’s world where AI and machine learning are reshaping how we interact with tech at lightning speed. For those familiar with SaaS, rapid, frequent releases are nothing new. Apple had the perfect ecosystem to pioneer this shift earlier but missed the mark, leaving valuable opportunities on the table with their delayed entry into AI-driven capabilities. At the pace GenAI and LLMs are evolving, a single year is practically a lifetime. By embracing more frequent, timely releases, Apple can course-correct and stay agile, catching up with innovation that’s moving faster than ever. #Apple #AI #TechInnovation #Agility

9

I've re-watched this clip of Matt Wood during Collision Conf a few times so thought it worth re-sharing. It's a helpful snapshot to understand the #generativeAI landscape... (not an exact quote but)... Different models from different providers each have different sweet spots. Some have different use cases that they’re really good at. Some are excellent at summarization, some perform well at analysis, others are really good at reasoning or code interpretation. Or they breakdown by different operational characteristics. Some are incredibly fast, others are low cost, and some are really intelligent. And what we’re hearing from customers that are applying generative AI to their use cases is you want to be able match the right use case to the right model.

131

4 Comments

AI everywhere is the buzz! How will it happen? We would have to move from System of Records to System of Cognition with Human in the loop. Note AI in its current form is a great automation enabler, simplifier of search + system interactions and more importantly a Decision Support System. What do you think, share your views in the comments 👇 and follow me (Vellanki Sriharsha) for more such insights. #AI #Automation #DecisionSupportSystem #GenAI

8

Interesting point of view on Apple's approach to AI. I believe that Apple approach is pretty thoughtful for the consumer space (that is generally grossly overhyped). I strongly believe that the real next frontier for LLM value creation is in developing LLMs for enterprise use cases that offer concrete practical value. This is very much an (yet) unsolved area! #GenerativeAI #largelanguagemodels #artificialintelligence #airevolution

56

5 Comments

Make an indoor map and embed it on your website in seconds. It really is this easy with Mappedin.

24

Thats the exact explanation I gave to a group of investors last week. (… it’s just Precision/Recall, attributes vectorization as “embedding”, K-Nearest Neighbor, User Search Intent, DAG, ML algorithms, etc all over again …). LOL and they asked what’s new this time around. And I was like not much, ML is still the backbone, and AI is the inference and actions based on the model. It works better when there is a feedback loop in a closed system. But the current state of the art like ChatGPT is based on scraping the Internet (garbage in, garbage out). Kinda like early search engines. What is a better analogy is that NVIDIA/Snowflake etc are selling tools, aka pickaxes to prospectors. The gold is up to you to find. And the opportunity right now is to monetize industry specific (healthcare, travel, financial services) clean data to build models with (aka a treasure map for the prospectors). From an enterprise perspective, what’s out there today aka generative AI isn’t very useful. Too much hype. To build useful engines will require an effort similar to search revolution 2 decades ago. From

16

3 Comments

TechCrunch covers Domino Data Lab joining forces with the LF AI & Data Foundation and Intel Corporation to initiate the Open Platform for Enterprise AI (OPEA) to foster collaborative development of #generativeAI systems: https://lnkd.in/gh3uKuJj #OPEA #EnterpriseAI #AI #genAI #ResponsibleAI #datascience #machinelearning #ml #mlops #EnterpriseAI #AIatscale

1

As technologists, we bear the crucial task of steering technology towards ethical usage. I am encouraged by the proactive measures Thorn, along with Amazon and other AI leaders, is implementing to establish safeguards in generative AI. The Safety by Design principles set essential standards to counter risks such as CSAM and AIG-CSAM, ensuring the safety of children. Learn more about these principles here: https://lnkd.in/e6XvQAVz

495

13 Comments

“Companies that aren’t prepared to take advantage of AI will fall behind” says Intuit’s CEO. The recent news about Intuit’s strategic investment in AI tells one story: AI is changing the landscape for incumbent companies, and those companies need to move fast to integrate AI into their business model. But it isn’t just the competitive landscape that’s changing. There’s also a slower change unfolding that’s just as radical: AI is changing how people actually get work done. Using AI can turn hours of daily manual work into tasks that are just seconds or minutes long, freeing up whole days to focus on impact. It can also spread information instantly anywhere across the globe, without a meeting. (Teams that are using Atlassian's AI features are spending 50% less time searching for information!) Using AI is a new opportunity to compete * and * a new way to execute. Link in the comments.

160

33 Comments

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

24

What a great post from Brett, our CEO and Co-Founder, about the transformative power of GenAI in the workplace. 🚀 In my view, GenAI brings multiple points of joy to employees: - Enhanced Efficiency: The joy of doing their jobs better and faster. ⚡ - Easier Learning: The joy of learning more easily. 📚 - Creative Expression: The joy of getting more of their ideas out into the world and making an impact. 💡 Many employees struggle with motivation due to monotonous tasks and feeling like just a cog in the wheel. 🛠️ AI addresses these challenges by automating the drudgery and enabling ideas to come to life more easily. 🌟 AI is presenting opportunities to improve work life. When people experience joy at work more often, they are more likely to be engaged, impactful, and loyal. ❤️ However, as Brett mentioned, companies must create the right culture for this transformation. 🌱 Helping employees demystify GenAI and truly understand how to use this powerful tool is essential to unlocking potential and ultimately bringing more joy into the workplace. 🤖 For more of my thoughts on this topic, check out my latest blog post here: https://lnkd.in/geHx3vFy, where I combine Brett's insights with my own ideas mentioned in this video. 🎥 Let's embrace the future with AI and make work a place of joy and innovation! 🌐✨ #AI #GenAI #WorkplaceTransformation #EmployeeEngagement #Innovation

3

🍜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

163

37 Comments

This old post from Ben Horowitz highlights a common struggle among entrepreneurs – expecting the team to perform seamlessly without investing in training. People are not plug-and-play; they bring diverse backgrounds and perspectives. You gotta spend time training and educating on your business, the way you want to talk to customers, and the right experience you want for them. Training is a powerful tool and needs to be done regularly! https://lnkd.in/ekv8c6WD #Entrepreneurship #Training #BusinessSuccess

6