Hamsa Buvaraghan

India is not just catching up in the AI race; we're innovating and leading in ways that are uniquely ours. The Economic Times recently highlighted how our approach to Generative AI goes beyond just Large Language Models (LLMs), addressing the specific challenges and opportunities within our diverse market. Rahul Agarwalla, Managing Partner at SenseAI Ventures, shared his invaluable insights into this AI revolution. His leadership and vision are truly driving innovation in the field, and it's an honour to be part of this journey with him. For anyone interested in the developments in AI and how India is making its mark on the global stage, this is a must-read.

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Generative AI and machine learning: two titans of tech, often confused but distinctly powerful. One creates, the other predicts. Both are reshaping industries at breakneck speed. Which will have the greater impact on your business? The answer might surprise you. #AI #MachineLearning #TechInnovation #BusinessStrategy #FutureOfWork What's your take on the AI revolution? Share your thoughts below.

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Generative AI: miracle worker or sophisticated guesser? While AI can now write, code, and create, it's essentially still a prediction machine. This revelation challenges how we view and utilize AI in business. What does this mean for your AI strategy? Let's discuss. #ArtificialIntelligence #BusinessStrategy #TechInnovation #AILimitations #FutureOfWork

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Diagram of Thought (DoT): An AI Framework that Models Iterative Reasoning in Large Language Models (LLMs) as the Construction of a Directed Acyclic Graph (DAG) within a Single Model https://flip.it/Mh_Mhu

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🌉 San Francisco's Surprising Comeback: From 'Doom Loop' to Renaissance? Recent data suggests that San Francisco, once trapped in a pandemic-induced 'doom loop', is showing strong signs of recovery. Here's what's changing: 📈 Positive Trends: - Population Growth: Net gains over the past two years, with domestic in-migration positive for the first time since 2012. - Housing Market: Median home sale prices up 1.2% YoY to $1,427,500 in June. - Job Growth: The Bay Area added 7,400 jobs between January and June. Downtown Revival: Foot traffic beyond typical work hours has recovered to over 90% of pre-pandemic levels. - Crime Reduction: Property crime down 32% and violent crime down 14% in Q1 2024 compared to Q1 2023. - AI Boom: The city is positioning itself as a hub for the AI revolution. 🚧 Ongoing Challenges: - High office vacancy rates - Homelessness and drug crisis - Lagging tourism and business travel 🔑 Key Initiatives: - "Vacant to Vibrant" program offering free rent to businesses in empty storefronts - Increased police patrols and encampment sweeping - Crackdown on open-air drug dealing 💡 Expert Insight: "The rising AI empire is giving the city a new edge. Funding, talents, and culture related to the AI revolution will help the city turn the corner." - Lu Chen, Senior Economist at Moody's Analytics 🤔 What's Your Take? Are these positive trends sustainable, or is it too early to declare a comeback? How can other cities learn from San Francisco's recovery strategies? What role will AI play in reshaping urban economies, particularly in tech hubs? https://lnkd.in/gCnPCBRU

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Ready for an #Agentic future where AI agents collaborate, adapt, and act autonomously? OpenAI announced the next frontier in Enterprise AI: "Swarm." It introduces the concept of agent chaining: If an agent cannot complete a task independently, it can delegate the task to another agent through a handoff. Want to learn more about Agentic AI? Attend the IIT Bay Area Leadership Conference 2024 this Saturday (October 19, 2024). Jeremiah Owyang will give a talk on "Agentic AI: Shaping Autonomous Future." The article mentions: "Swarm’s release has also rekindled debates about the ethical implications of advanced AI systems." You can attend Brian Green's "Ethical Decision Making In the Age of Data and AI" talk to learn more. It mentions: "Security experts stress the need for robust safeguards to prevent misuse or malfunction in networks of autonomous agents." You can attend two sessions: (1) "Driving Business Innovation: AI, Zero-Trust, and Investment Insights" by Mario Espinoza (CPO of Illumio), Dr. Vipin Chaudhary (Prof and Chair at Case Western University), Hitesh Sheth (CEO of Vectra AI), and Pramod Gosavi (Venture Partner at Blumberg Capital) and (2) "Gen AI: Data Security and Privacy" by Dr. Anand Kashyap (CEO at Fortanix), Nilesh Thakker (President at Zinnov), and Dr. Anirban Ghosh (AI/ML Consultant at Infosys). The article mentions: "The specter of job displacement adds another layer of complexity," and you can attend the session "Future of Work in the Age of Data and AI: VCs' Perspectives" by Ashmeet Sidana (Engineering Capital), Raviraj Jain (Lightspeed Ventures), Apoorva Pandhi (Zetta Ventures) and Lochan Alagh (VC Nest). And, of course, there are many more sessions. Register here: ttps://lnkd.in/gRUVzbfA #Leadership #IITBayArea #TechIcon Speaker Affiliations: Databricks, Glean, Sapphire Ventures, Accenture, Illumio, SAP, Okta, Birlasoft, Infosys, Vectra AI, Fortanix, Postman, Workato, and many more Nidhi Kannoujia, Arnab Debnath, Ashis Khan, Anshu Agarwal, Swapnil Sinvhal, Lochan Alagh, Rao Charagondla (CNR), Dipty Desai, Ph.D., Praveen Vayalamkuzhi, PhD, FRSA, Surbhi Kaul, Ishita Sharan, Hrishikesh Sathawane, Bidyut Parruck https://lnkd.in/gJwa_ZXJ.

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AI memory is fundamental for conversational AI and AI agents. It is critical for building personalized experiences and improving reasoning. Check out Letta’s course to understand how to use AI memory to enhance the customization and quality of your AI app.

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We are quickly entering the "trough of disillusionment" in the hype cycle for generative AI. While GPTs excel in automating certain tasks (and can even automate away large portions of some jobs) they often fall short in others. Like all new technology, the issue lies in misapplying generative AI for tasks it wasn't designed for. This is a problem compounded by the GPTs themselves suggesting they can handle these tasks (often cheerfully!). This misalignment creates frustration and unmet expectations which we're starting to see more of these days. As the dust settles I firmly believe we'll recognize GPTs as a transformative technology across many industries. However it's crucial to understand their limitations and apply them appropriately. What are your thoughts on the current state of generative AI and its future applications?

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Incorporating Generative AI into business workflows presents immense opportunities, but managing its hallucinations—when the AI generates inaccurate or misleading information—is crucial for long-term success. Unchecked hallucinations can erode trust, misinform decision-making, and expose businesses to reputational and financial risks, particularly in industries like healthcare where precision is non-negotiable. By implementing robust safeguards such as fine-tuning models on domain-specific data, integrating human-in-the-loop systems, and reinforcing AI outputs with fact-checking mechanisms, businesses can mitigate these risks. Our latest report highlights our point of view on how the hallucinations can be effectively managed.

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At a Generative AI thought leadership dinner with other CTOs in NYC today and some interesting trends are emerging: * a consensus that LLMs are converging on a general set of features and basically comparable performance * a consensus that an org's data pipelines will matter more than the LLM chosen * and a group of people who read the TOS that are really scares about what these LLMs will do with access to all your data. Lastly, my prediction: the work of tech is moving from the keyboard to the whiteboard. Ai as microservice means structuring your data, thinking with ai, and chaining ai agents will supercharge your career and your cause -- but only if social change orgs platform their data. In my study of polymaths, Charles Babbage designed the basic idea for a unit of computing being something that takes an input, does something to it and gives an output -- the so called Babbage difference engine. In a real way, GenAI is approaching a world where chaining inputs ala a babbage difference engine is accessible to all. This can be an awesome opportunity if we get Non profits to work together!

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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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Generative AI is spreading like wildfire. 💡 Nearly 40% of US adults have embraced it in just months - outpacing the adoption of PCs and the internet. This tech revolution is reshaping how we work and live. Are you ready? #GenerativeAI #TechAdoption #FutureOfWork #AIInnovation #DigitalTransformation What's your experience with generative AI? Share your thoughts below!

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🤖 💔 What can go wrong with LLMs? Have you thought about shipping an LLM application but wondering what can go wrong? Ryan Luo and I will break it down for you in 3 easy categories: 1. Correctness 2. Quality 3. Safety ❗ Correctness: We've all seen LLMs can return factually incorrect responses, but fixing the issue can be difficult. The most common example are hallucinations, where a model confidently returns factually incorrect responses. Some techniques to mitigate correctness risks include RAG, fine-tuning, and prompt engineering. ❗ Quality: Sometimes LLMs create a factually correct response, but don't achieve the initial goal set by the developer. Especially in complex agent workflows, quality must be evaluated to compare LLM application efficacy with existing solutions. ❗ Safety: Content safety is a new area for LLMs. Your LLM agent may return offensive content, leak sensitive data, or be vulnerable to adversarial prompt injections.

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AI, much like past transformative technologies, holds the potential to reshape our work landscape, particularly in fields such as compliance, where automating monotonous tasks could bring about significant changes. When considering AI, it's crucial to address fundamental queries: - Is it accurate? - Is it reliable? - Is it worth the investment? These questions serve as checkpoints rather than obstacles. Given the importance of regulations, utilizing AI to enhance efficiency necessitates a thoughtful approach. To achieve success: - Emphasize transparency. - Incorporate human oversight and accountability. - Establish robust auditing procedures. Finding the right balance between AI capabilities and human discernment is paramount. Let's welcome innovation while ensuring it is implemented effectively. https://lnkd.in/exCzQP7d

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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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📈 AI Startup Sierra Expands HQ in San Francisco (4K to 41K SF) 🌁 Artificial intelligence firm Sierra is making a bold move by relocating to a larger office within San Francisco. The startup has signed a lease for a 41,104-square-foot space at 235 Second St., significantly upsizing from its current 4,000-square-foot office. 🏢 This move to San Francisco's South of Market neighborhood, where office vacancy rates have started to decline for the first time since 2020, is a positive sign for the city's hard-hit office market. The area's office vacancy rate, though still high at 28.8%, is slightly lower than six months ago. 📉 The deal contributes to the increase in leasing activity in San Francisco, which is up by about 1 million square feet compared to last year. This uptick is driven by the region's reputation as a leading national hub for AI companies. 💼 Sierra joins other AI firms expanding in the South of Market area, including Scale AI, which signed the city's largest office lease of 2024 with a 178,000-square-foot deal. So far this year, office tenants have signed leases totaling 750,000 square feet in South of Market, a significant increase from last year's 370,000 square feet. 🚀 Co-founded in 2023 by former Salesforce CEO Bret Taylor and former Google executive Clay Bavor, Sierra raised $85 million earlier this year to develop a customer support AI tool for businesses. The firm is set to relocate from its current space at 215 Second St. by next month. San Francisco's reputation as an AI hub, bolstered by its talent pool and six major AI research institutions, continues to attract companies. Recent significant deals include OpenAI’s sublease of over 400,000 square feet of Uber’s former headquarters and Anthropic’s takeover of Slack's former headquarters. These developments reflect a resilient and adaptive real estate market. As a commercial real estate professional, I’m excited to see how these trends shape the future of office space in our vibrant city.

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