Hamza Farooq

Had a great conversation with Jabari Young from Forbes about the $13.8 million AI Squared just raised in Series A funding, led by Ansa Capital and New Enterprise Associates (NEA). It’s exciting to watch AI Squared grow, because helping organizations deploy and streamline their use of AI is something I’ve been working on for a long time. During my time at the National Security Agency, I started thinking on how to accelerate and streamline the way organizations adopt AI. Leading their data science team, I saw first hand that many of the AI/ML solutions developed were never actually able to keep people safer - and that mattered to me, because I had two brothers deployed overseas. I knew then I wanted to fix this problem. I went to Databricks to better understand how to incubate a technology and bring it to market - and worked with Matei Zaharia, Ali Ghodsi, Ion Stoica, Pete Sonsini, Greg Papadopoulos, Luke Cooper and so many others who helped me understand what it is to build a great business. I work now with talented people who bring experience from the data science and technical teams of Microsoft, JPMorgan Chase & Co. Chase and the United States Department of Defense, and I am grateful for the growing number of people invested in AI Squared’s success. As part of today’s investment, Roger W. Ferguson, Jr., former Vice Chairman of the Federal Reserve and board member of Alphabet Inc., has also invested and will join the company’s Board of Directors. Ansa Capital co-founder and General Partner Allan Jean-Baptiste will also join AI Squared's board. I’d like to thank Ansa Capital for leading this funding round and existing investors New Enterprise Associates (NEA), Latimer Ventures and Ridgeline. We’re excited to use this funding to expand our team and mature our platform - because we’re invested in helping businesses truly maximize the value of AI. Read more about the funding round and AI Squared of Forbes here: https://lnkd.in/edTdauaZ

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This year is not only the year of AI, with two Nobels and unprecedented growth in LLMs, but also the year of India -which is likely to end the year as the fastest growing of large economies. So it is indeed humbling to be hosting India's first-ever AI conference focused on the Indian financial industry that is enabling that very economic growth in the city of Mumbai on Nov 26th of this year. At L&T Finance we are pioneering use of AI/ML, including both Generative and Predictive AI, in ways and on data that have not been attempted not only in India, but in the world. We will share our vision of what we are doing, and also bring together some of the top thinkers and doers in BFSI and in AI not only in India, but from across the world in this first edition of the R.AI.SE conference. There will be talks and panels on AI's potential in India's development (Vikshit Bharat), to how AI is being used in the real world to transform banking, lending, fintech, and a lot of other industries in India, Southeast Asia, EMEA, and beyond; to how regulators in India are thinking about AI, to the socio-economic impact of AI in India, to how AI improves functions as diverse as UX to Underwriting, and technical masterclasses and visions of the future of AI from industry leaders. Come join us in this first-of-a-kind event by registering at http://www.ltfraise.com RAISE: AI-for-BFSI Conference. On Nov 26th, 2024, at Jio World Center, Mumbai, India. Hosted by L&T Finance #AI #India #Fintech #BFSI #conference

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Interesting insight from Santosh Rao on Marketplace by APM My research talks about metrics Tech/SaaS Leaders should measure depending on your scale https://lnkd.in/gGfBWgn5

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LinkedIn team (Juan Pablo Bottaro Karthik Ramgopal) shared a helpful deep dive into their deployment of an LLM-powered job search assistant. Highly recommend this read! Few highlights:  💡 Relatively easy to setup RAG-based pipeline. Achieved 80% of the basic experience in 1 month, then 4 more months to reach 95% mark. 💡 Evaluating the quality of application outputs is hard. I hear this from many enterprises developing LLM applications. (check out Okareo by Matthew Wyman Boris Selitser) 💡 Balancing latency with quality is important. While certain techniques like Chain of Thought could improve accuracy and reduce hallucinations, it will increase response times, which can affect user experience. https://lnkd.in/gtGGwf5P #largelanguagemodels #RAG #EBR #LLM #ml #ai #hallucinations #evaluations #

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A conversation from 2020: "I'm thinking about entering the data warehouse market" -Ali Ghodsi, Databricks CEO "That's the stupidest idea I've ever heard" -His expert advisor Today: That "stupid" idea generates $600M annually. In venture, we worship expertise. But expertise is rear-view wisdom. Innovation happens in the blind spots. When a founder sees something you don't, pay attention. They might just be early. You might just be wrong. -- Check out my Newsletter - TheFoundersCorner via the Link on my profile page or the Link at the top of the page ☝️ Jam Packed with Actionable Insights Every Week 💙

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Tabrez Syed keeps sharing more insights in the AI ecosystem, the new developments, the movers and shakers. In this week's blog, Tabrez shares some staggering statistics kind of favouring why Google will win the AI search war. Here are some numbers from the article: "..... the scale of their data collection is mind-boggling. Gmail serves 1.8 billion users who send 121 billion emails daily. Google Photos stores 13 petabytes of images, enhanced with 2 trillion user-generated tags. This massive data advantage isn't just about quantity - it's about variety and quality. While competitors might have access to public web data, Google has two decades of refined search queries, user behaviors, and cross-platform interactions......" I guess I am going for the new Pixel 10 Pro as soon as it arrives :) #searchengines #searchAI

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How does LilyHan AI approach solving such a business critical problem associated with Large Language Models (LLMs) & concept of hallucination? As the Founder, my primary mission has been to address the monumental challenge of resolving hallucinations in Large Language Models (LLM). The deeper our team delves into this issue, the more complex it becomes. It is essential for us to determine how to commercialize a product that reliably supports mission-critical business decisions for its users—a challenge we welcome. From my perspective, a successful defense against hallucinations involves not just one technique, but the harmonious combination of several strategies. The critical insight is to blend these tactics smoothly into a cohesive plan, and then integration of the exact plan into the products we build to attain the outcomes our clients desire. This includes leveraging SOTA Evaluation frameworks and working with subhojit banerjee (ML Engineer) and Satvik Paramkusham , who are some of our esteemed advisors for our project. To add, one of the foundational whitepapers (A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models by SM Tonmoy  et al· 2024) will serve as a guide through that our project approach. This paper covers how to tackle hallucinations by breaking it down into three parts: getting the data ready, training the model, and checking the model after it's trained. It also highlights that using Reinforcement Learning from Human Feedback (RLHF) and systems based on knowledge can really help in cutting down on hallucinations - which implies emphasis on software engineering, data quality approaches, and a human centric approach. Our approach, starts with a straightforward use case to establish a baseline. From this foundation, we continue to develop additional use cases tailored to the diverse risk tolerance needs based on our clients' needs. From a Product/Platform perspective, it is critical to maintain the agility of our products by integrating new techniques and research as they emerge. This continuous improvement will allow our AI solutions remain at the forefront of industry standards. Special commendations go out to NIKHIL AGARWAL and Shikhar Amar for this project along with our advisory team.

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Top 5 LLM Testing and Evaluation Tools: 🔭 Galileo: An end-to-end platform for GenAI evaluation, experimentation, and observability AgentOps.ai: Build reliable AI agents with monitoring, testing, and replay analytics. Toloka: A data-centric environment to support fast and scalable AI development with the help of human insight. Gantry: Powerful observability, analytics, and evaluation for your AI-powered products. RagaAI Inc: Fix AI issues in three easy steps - Detect, Diagnose and Fix. #AI

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Focusing on integrating data efficiently will be key to harness AI's full potential. Yes, there are many challenges, but at Tray.ai, I've seen firsthand that AI success demands embedding innovation into an organization's DNA. Empowering employees to develop and deploy AI solutions rapidly is vital. Companies that prioritize swift experimentation and iterative processes over flawless implementation will build resilient AI capabilities, ready to evolve with market demands. Learn more here in my interview with TechdayUK : https://lnkd.in/esgD9kiG

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The first episode of Metadome.ai's "Into The Verse" podcast is live.   In this episode, Sagar K., Rahul Ranjan Srivastava, and I have covered everything from the inception of #XR to a future where #VR headsets are the norm. Check it out on YouTube- https://lnkd.in/gEDX87AT #AR #IntoTheVerse

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Interview with Gurudev Karanth, the CEO of OutOfTheBlue.ai Bootstrapping data startups: Creativity + Adventure spirit is the way out of the "lack of early data" desert --- Imagine that you are dropped into the middle of the desert. You have just about enough food to make out of the desert. However, getting out of the desert is your problem because no one can help you. This is the life of a typical entrepreneur. Things get more challenging for an AI/data startup. You need data to build a solution for a company, but you need the company to send you their data first. Every data company must solve this bootstrapping problem. It's like being dropped into the desert without a map; first, you must establish your bearings. Hear how Gurudev solved this problem, his thoughts on the challenge in eCommerce space that compelled him to start OutOfTheBlue.ai, and critical principles for being an entrepreneur. 

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In an exciting wave of developments, SAS, renowned for its prowess in data and AI solutions, has unveiled what they're calling a game-changing approach to tackling business challenges. The introduction of lightweight, industry-specific AI models for individual licensing sets a new-era beacon. It embodies SAS's ambition to democratize AI - making it accessible regardless of one's skill set. Some thoughts on why such a move is transformative: • It disrupts the traditional approach by placing ready-to-deploy AI technology directly into the hands of organisations. This could mark the dawn of an era where AI integration into businesses becomes the new normal rather than a distinguished edge. • The idea of industry-specific AI models undermines 'one-size-fits-all' and acknowledges the unique needs of each business sector. It can potentially ensue a wave of diversified innovations in different industry niches. Consider the vast spectrum from healthcare to entertainment to finance - each one will have a model suited to their unique challenges and needs. • It is not just about easy access, but also about efficient productionisation of real-world use cases. Given SAS's expertise in AI, these models could well fill the demand-supply gap in AI technological requirements, setting a new track record in driving productivity with speed and efficiency. As Chandana Gopal, Research Director, Future points out, this could be a big boost towards making AI accessible to businesses of all scales. In light of this, my prediction is two-tier: 1. We would witness an upsurge in the adoption of AI technology across businesses – be it multinational corporations, local enterprises or startups. 2. Given the industry-specific approach, I anticipate AI-related breakthroughs nurturing sector-specific innovations leading to enhanced customer experiences. #AI #Technology #Innovation #businessstrategy #SAS #ArtificialIntelligence

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If you are interested in building a GenAI application from scratch quickly, you may want to check out this AI-powered app building guidance #chatbot. Built by Epsilla (YC S23)'s #nocode #genai agent platform, this intelligent chatbot with provides comprehensive answers to your inquiry with clickable links to useful tools covering every step of your needs: from research, feature design to actual implementation and deployment. Underneath it, it leverages a sophisticated chain-of-thought workflow combined with other customizable components to orchestrate the best answer possible grounded by trusted sources. Even if you are not in the app building mood, you can still try it out and experience the power of such an app and think of other useful GenAI apps you may want to build with the underlying platform.

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AI adoption continues to accelerate, becoming self-sustaining and evolving independently of human intervention. #AI #AIAdoption #BuboDefense

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AI-powered knowledge management is revolutionizing productivity, as highlighted in Sirjad Parakkat's insightful article. It's essential reading for understanding AI's potential in transforming traditional systems. Our "Tailored Intelligence" consultancy and tech services go further by ensuring that private data is not used to train public AI tools and keeping human experts in the loop. We combine AI's power with human insight to protect your proprietary knowledge and enhance decision-making. Discover how we take AI-driven knowledge management to the next level. #tailoredintelligence #ai #artificialintelligence #digitaltransformation #aiinsociety #impactai #innovation #visionaires #business #wikiexpert #solutions

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I had an engrossing conversation with Jason Lopatecki, CEO and Co-Founder at Arize AI, who joined me for the latest episode of the ODSC’s AI X Podcast! In this episode, we explored the complexities and opportunities of evaluating LLMs, AI Agents, and RAG. With the growing use of GenAI, getting evaluation right is more important than ever, and Jason shared some great insights into how to navigate these challenges. Topics we discussed include: 🔹 Evaluation-driven development – how defining evaluation criteria before building can set a project up for success. 🔹 Agent Control Flow – breaking down AI agents into manageable components and evaluating the decisions made at each step. 🔹 Open-source vs. proprietary models – weighing the risks and benefits of each when deploying GenAI in real-world applications. 🔹 AI as-a-judge – leveraging LLMs to evaluate other AI models and workflows. 🔹 RAG evaluations – ensuring retrieved information is accurate and relevant to the task. Don’t miss this chance to dive deep into the ins and outs of GenAI evaluations. 🎧 Listen Now: https://hubs.li/Q02T5vQp0 #AI #Podcast #ODSC

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Are you grappling with the complexities of deploying Machine Learning models at scale? Harshit Agarwal from Faire will share an insightful session that delves into real-world ML infrastructure 🔍 Key Topics: - Optimal structuring of ML serving and deployment infrastructure -Integrating robust testing and observability into your ML pipeline -Crafting production-grade tools that data scientists and MLEs will adore -Scaling ML to serve users effectively: A deep dive into design choices 🤔 Why is this important? In today's data-driven world, the ability to deploy and serve ML models efficiently can make or break a company's competitive edge. This talk is crucial because it: - Bridges the gap between ML theory and practical implementation - Addresses common pain points in ML deployment that many organizations face - Offers insights into building scalable, reliable ML infrastructure - Provides strategies for improving collaboration between data scientists and engineers - Shares real-world examples and lessons learned from a successful e-commerce platform Whether you're a data scientist, ML engineer, or tech leader, this talk will equip you with valuable insights to elevate your ML deployment strategies. #MachineLearning #MLOps MLOps World Generative AI World Summit

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