Tenstorrent Inc.

Responsible for new product launches and packaging the hardware products with right software to provide world-class user experience to AI/ML developers on noble AI hardware architecture.

• Led the launch of the first-gen AI accelerator Grayskull cards by piecing together the hardware and
software components into a unified product.

• Built a flourishing community around opensource source software stacks TT-Buda and TT-Metallium
specifically designed to leverage Tenstorrent hardware.

• Led the development of consumer facing TT-Studio, a low-code product that makes it super easy to
deploy and fine-tune AI models on Tenstorrent hardware.

Senior AI Product Manager

Responsible for onboarding developers to the Tenstorrent ecosystem and build a flourishing community of AI developers around the AI accelerator cards and systems. Acted as a bridge between the developers and engineering to understand and solve end-users pain points.

• Established partnerships with leading cloud AI providers to simplify AI model deployment on Tenstorrent hardware through straightforward APIs.

• Developed and implemented Tenstorrent’s social media and content marketing strategy to educate end-users about alternative AI hardware benefits. Also, founded the Tenstorrent developer community,
fostering direct developer engagement in product development.

• Led the development of an AI playground to demonstrate AI model capabilities on Tenstorrent hardware, enhancing product visibility and engagement with potential customers.

Head of Developer Relations

Packt

Co-authored the book "GPT-3: The Ultimate Guide To Building NLP Products With OpenAI API" which explores Generative Pre-trained Transformer 3, a powerful LLM developed by OpenAI in 2020, the predecessor of ChatGPT. The book is a blend of technical and business knowledge summed into a manual that could be the start of your AI journey.

The book aims to reduce the friction between ideas and execution and bring people from all backgrounds into the AI ecosystem. It features the behind the scene story of building OpenAI API, GitHub Copilot and Azure OpenAI Service from the creators themselves. 

Order now 👇

Co Author

Co-authored the book "Neural Search - From Prototype to Production with Jina". It's an in-depth guide to building deep learning–powered search systems that you can deploy and manage with ease.

Order Now 👇

Unwind AI

Daily AI Newsletter read across 49 US states & 146 countries by over 10,000 AI professionals.

Exclusive, bite-sized AI wisdom packaged as a 3-minute Daily AI Digest - directly from the field to your inbox.

Creator and Writer

Jina AI

Responsible for transforming the developer experience for Jina ecosystem and driving awareness of Jina AI products. Owned relationship with developer community and ensured seamless onboarding and accelerated learning for developers of all skill levels.

• Led the development of Jina’s Developer Portal, facilitating efficient onboarding of new developers to the Jina AI ecosystem.

• Created developer-friendly content pipeline for neural search, cross-modal/multi-modal applications, and LLMs.

• Enhanced the developer experience within the Jina ecosystem by analyzing user journeys to identify and alleviate pain points, enhancing practical usability.

Senior AI Evangelist 

Responsible for building and leading a community of open-source developers in the neural search domain,
while creating documentation and examples that ensure smooth developer onboarding.

• Drove significant growth in community engagement, increasing Slack membership, GitHub stars, and
forks by 4-5x within a year.

• Built and led an open-source developer community in neural search, consistently making Jina a top
trending project on GitHub.

• Developed extensive documentation and practical examples to ensure smooth user onboarding,
effectively collaborating with engineering and product teams to integrate community feedback into Jina's
roadmap.

Developer Relations Specialist 

Kairos Data Labs

Kairos Data Labs originated with the idea to accelerate innovation through the widespread adoption of AI. We help individuals and companies to realize their true potential by leveraging AI.

Kairos Data Labs provide niche consulting services to the Fortune 500 companies, startups, and individuals to innovate the next generation of their product ecosystem by leveraging coming-of-age technologies like GPT-3.

Co-Founder

Vocable.ai

Responsible for:
• Laying out the roadmap for product vision and development.
• Architecting the technical stack and ensuring its smooth integration with the OpenAI ecosystem.
• Ensuring smooth user onboarding and a flawless experience with the AI content marketing tool.

AI Advisor

256.Network

256 Network is an exclusive, invite-only network that brings together the global industry leaders in the investment space (VCs, CVCs, PEs & Sovereign Funds) with the mission to allow collaboration across industries and firms without any fiction. The north star of the 256 network is to solve the trust deficit in interaction and cooperation across industries on a relationship-first basis. 

We work with over 600 members from the Asia Pacific, the Middle East, Europe, and the United States holding prominent positions across sectors and firms. I am responsible for leading the data initiative at 256.network, to build a data-driven ecosystem of global decision-makers investing in the startup ecosystem.

Interested in knowing more about the 256 Network, drop me an email at shubham@twofiftysix.network or visit http://www.twofiftysix.network

Data & Strategy

Arcesium

Responsible for establishing the machine learning practice from scratch at Arcesium, a leading post-trade technology and professional services firm supporting over $675 billion in client assets.

• Founded the ML practice from scratch and rapidly scaled the team to 10 data scientists within a year.

• Implemented an NLP-based ticket triage and resolution system company-wide, significantly improving
efficiency and reducing response times.

• Developed an ML-powered solution to automatically identify breaks in reconciliation and provide
detailed tracebacks, saving hours of analysts’ time.

Data Scientist

Augmented the existing ticketing system with an NLP-based Ticket Triage feature which minimized the manual intervention and reduced the ticket resolution time by manifolds.

Implemented an NLU-based semantic search for Smart Recommendation of semantically similar tickets to eliminate the toil in logging and reviewing the already resolved tickets.

Data Science Intern

Tata Consultancy Services

Developed an Automated Credit Risk Assessment Strategy which resulted in the reduction of lending time from one week to three days.

Built from scratch an ML-powered system for automatic flagging of defaulters which resulted in significant improvement over the conventional method for classifying the defaulters.

Machine Learning Intern

🥑 AI Product Manager at Tenstorrrent focused on bridging the gap between state-of-the-art software and the specialized hardware built for AI. 

📕 Co-author of "GPT-3: The Ultimate Guide To Building NLP Products With OpenAI API" and "Neural Search - From Prototype to Production with Jina"

🗞️ Run a daily AI newsletter "Unwind AI" that delivers the latest AI developments and best AI tools directly to your inbox.

🤝 Senior AI Evangelist at Jina AI responsible for building the next generation of AI ecosystem for developers to build and deploy multi-modal/cross-modal applications in the cloud.

🤖 Co-founded Kairos Data Labs to minimize the gap between state-of-the-art AI innovations and applied AI applications within organizations. Our mission is to accelerate innovation with the widespread adoption of AI.

👨‍💻 Founding Data Scientist responsible for creating organization-wide data strategies and infrastructure to build & scale the data science and machine learning vertical within Arcesium (The DE Shaw Group). Built state-of-the-art AI solutions in the area of post-technology services for the biggest hedge funds of the world.

💵 Lead the data initiative at 256 Network, to build a data-driven ecosystem of global decision-makers investing in the startup ecosystem.

📈 Part of the founding cohort at Plaksha's Tech Leaders Fellowship (https://plaksha.org/techleaders)

🤝 Let's Connect: Follow me to stay on top of what's happening in the AI world. Your next insight or inspiration is just a connection away.

GraphRAG: Teaching LLMs to Connect the Dots 📚

Ever felt like your AI assistant just doesn't get the big picture?

Traditional RAG systems are like that friend who remembers random facts but can't quite piece them together.

Meet GraphRAG, Microsoft's clever solution to help LLMs see the forest, not just the trees.

Imagine trying to solve a puzzle with pieces scattered across different rooms.
That's what traditional RAG does - it finds individual pieces but struggles to put them together.

GraphRAG creates a map of how all the information fits together. This means LLMs can now understand connections and context in ways they never could before.

What all GraphRAG can do? 

1. Uncover Hidden Connections
GraphRAG is like a detective, finding links between facts even when they're spread out. It helps LLMs tackle complex questions that require understanding how different pieces of info relate to each other.

2. Pinpoint Accuracy
 GraphRAG uses its knowledge map to find answers that are spot-on and make sense in context. Plus, you can trace each part of an answer back to its source.

3. Unlock Meaningful Insights
GraphRAG doesn't just fetch facts, it sees the big picture. It can spot trends, identify themes, and offer insights that would be near impossible to find otherwise.

Why This Matters for You?

Think about how often you've asked an AI a question and gotten a response that's... close, but not quite right.

Or worse, an answer that's just plain wrong.

GraphRAG could change all that. It's about making AI assistants that truly understand what you're asking and can give you answers that actually help.

What's Next?
As GraphRAG like developments mature, we might see:
• More intuitive AI assistants that can handle complex, multi-step questions
• Better automated research tools that can draw insights from vast databases
• AI systems that can explain their reasoning, making them more trustworthy and useful in fields like medicine or law.

Shubham Saboo

OpenInterpreter uses Mistral AI's Codestral running locally on your computer (100% free and without internet).

AI agent uses LLM and vision capabilities to autonomously control the computer. Just by showing a sticky note and a prompt, the AI agent automatically connects computer to the Wifi.

And this is just a start of what local AI agents can achieve, the possibilities are endless.

Video by Open Interpreter team.

Build a RAG pipeline using Mistral or Llama-3 running locally on your computer without wiring a single line of Python Code (100% free and without internet):

Meet GPT4All 3.0: The Open-Source Local LLM Desktop App

Experience complete privacy with support for thousands of opensource LLMs and major operating systems. All with the MIT licence.

Run Llama-3 on someone else's computer using world's largest peer-to-peer network for AI agents (100% free)

Follow these 4 simple steps: 

Step 1: Go to https://aios.network
Step 2: Simply install the client app on your laptop
Step 3: Open the app on your laptop
Step 4: Install "Llama-3" from AI models or use the model running on someone else's machine.

Microsoft just released 18 FREE courses on Generative AI for beginners. 

The courses include prompt engineering concepts, building LLM apps in Python, RAG, AI agents and vector databases. 

Each course includes video tutorial and step-by-step Python code walkthrough.

Claude Sonnet 3.5 transforms a simple PDF earnings report into an interactive dashboard in just 30 seconds. 

It goes beyond the capabilities of GPT-4o, Gemini Pro, Llama and other existing LLMs. 

Future of work will 10x more productive with AI.

Claude Sonnet 3.5 Opensource artifacts UI that you can use with ChatGPT, Gemini, Llama-3 or any other LLMs.

You can modify the existing code to work with ChatGPT or even Llama-3 offline. It consist of three key components: 

✅ LLM of your choice (OpenAI/Anthropic or Local LLM via Ollama) 
✅ Code Interpreter SDK for LLM code execution in sandbox environment
✅ Vercel AI SDK for tool calling and streaming responses from the model

It currently supports running Python code with support for JavaScript, R, Nextjs coming soon.

Claude Sonnet 3.5 can now search the web and generate images with ChatLLM. 

With just $10 you can use Claude Sonnet 3.5, GPT-4o, & Llama 3 in a single AI playground. 

Plus, build custom AI agents with RAG without writing a single line of Python Code.

First month is free, try it out now: https://lnkd.in/dUiXNBUS

AI Visual Studio Code Extension that lets me write optimized Python code for LLM apps, AI agents and RAG apps without running into errors. 

Traycer is an AI extension that provides me with smart, real-time feedback as I code. It stays in the background & appears only when need it the most.

It's not just another code generation tool that disrupts my workflow

Traycer not only identifies code that can be improved but also engages in a back-and-forth conversation about the reasons & methods, like having a senior AI engineer available 24/7 while you code.

Best part? Traycer AI is is FREE forever for open-source projects.

Claude 3.5 Sonnet transformed a simple prompting guide into an interactive prompt engineering cheatsheet in just 30 seconds.

Now, you can convert any PDF or static documentation into interactive learning materials in seconds with AI.

Content Creation will never be the same again with AI.

The Journey of an AI Engineer: 5 Lessons that I learned along the way.

Ever wondered what it's really like to be an AI engineer?

I've been there and done that. I want to talk about five crucial life lessons that you might already know but are important to remember as an AI engineer.

1. Embrace the Chaos (Or How I learned to stop worrying about the mess around me) 

Remember when you first learned to ride a bike? That's AI engineering in short. You're gonna fall. A lot!

But those falls? They're your best teachers.

↳ Expect the unexpected: AI models are like toddlers. They'll surprise you in ways you never saw coming. 

In my first job, I was tasked to build an AI Ticket Recommender (kind of Jira + AI). I created a Bert based classifier and recommender model, but I completely overlooked the jargon and technical terms in the text. The result? A model that confidently suggested completely irrelevant tickets, leaving everyone scratching their heads.

↳ Learn to love debugging: It's not a chore, it's a treasure hunt. The more you do, the better you get.
↳ Celebrate the small wins: Fixed a small bug? That's worth a victory dance.

2. Never Stop Learning (Or How I became a student for life)

In the AI world, the moment you think you know it all, you're already behind.

AI moves at super fast speed and I realize it every single day as part of writing Unwind AI daily AI updates. 

I have made it a practise to spend 2 hours daily: 

↳ Trying out 2-3 new AI tools 
↳ Creating one AI workflow that automates a small part of my work or increase my productivity. 
↳ Reading community discussions on Hackernews and Discord. 
↳ Writing daily about AI on LinkedIn and X

3. Collaboration is Your Superpower (Or How I learned I'm not as smart as I would like to think)

I used to think I could do it all solo. But I was very wrong.

The best work happens with the best team. But how to build or be the part of the best team: 

↳ Share your knowledge: What goes around comes around.
↳ Ask for help: Nobody expects you to know everything.
↳ Diverse teams win: Different perspectives lead to better solutions.

4. Balance is Must (Or How I realized that computers don't hug back)

Two years into my career, I was juggling over ten tasks at once, leaving no time for my mind to rest. I thought I was moving at an unconventional speed, but a year later, it hit me hard. My health suffered.

↳ Now I strictly make sure, that I spend atleast an hour outdoors walking or running or just sitting in the park. I literally schedule that as "stare at the wall" time. It's amazing what your brain comes up with when you do nothing.

5. Bring out the Story Teller in You (Or How I became the AI Guy at Gatherings)

↳ Writing about what you learn or do really helps. When you write think about how will you explain an AI topic X to a person Y with no context or background of the field. I get to do it everyday with Unwind AI and with my social posts.

It's already been a super long post 👋

Claude Sonnet 3.5 creates an Audio visualizer from a simple text prompt in just 30 seconds. 

Claude Artifacts increases it's applications by 10x compared to GPT-4o, Gemini, Llama-3 or other existing LLMs.

Claude Sonnet 3.5 transforms simple event details into an interactive event planning dashboard in just 30 seconds.

It hugely surpasses the AI event assistants you can create with GPT-4o, Gemini, Llama and other existing LLMs.

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