Suku Krishnaraj Chettiar

Fantastic panel on GTM for Enterprise AI. Thanks to fellow panelists for a sharp discussion and to Emergent Ventures for hosting. Anupam Rastogi Ankur Jain Preethy Padmanabhan Chandini M Ammineni Jason Griggs Deb Bardhan #GTM #EnterpriseAI

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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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𝗧𝗵𝗮𝗻𝗸 𝘆𝗼𝘂 ETCIO 𝗳𝗼𝗿 𝗮𝗻 𝗮𝗺𝗮𝘇𝗶𝗻𝗴 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗼𝗻 "𝗙𝘂𝗲𝗹𝗶𝗻𝗴 𝘁𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗛𝗼𝘄 𝗚𝗲𝗻𝗔𝗜 𝗶𝘀 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝗶𝘇𝗶𝗻𝗴 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀!" I am in sync with Tara Lodh, Customer Engineer, Google Cloud when he says he is excited about the voice perspective when it comes to GenAI Voice, as per his vision, will be used in: • code generation • workflow generation • even in the way we use search • day-to-day activities His data strategies are also very well-thought-out: • 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 & 𝗖𝗼𝗻𝘀𝗼𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻: Data is all around flowing all around systems, departments and processes. Therefore, high chance of duplication is there. So, number one strategy should be to break this replication as it can lead to errors and inefficiencies.   And consolidate data as it leads to unification to a centralized platform as it'll ensure that all teams can have access to consistent info. • 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗮𝗿𝗼𝘂𝗻𝗱 𝗗𝗮𝘁𝗮: There should be policies and standards to manage data securely and ethically. Compliance ensures protecting sensitive information and maintaining accountability for data usage. • 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Scalability depends on having solid foundation of quality, consolidation, and governance around data. Growth isn’t just about handling more, rather it’s about handling more effectively and responsibly.    • 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲: It's about maintaining speed and reliability while managing increasing demands. This is directly related to clean, accurate data that is unified across systems and managed with compliance. Manish Kumar's, Customer Engineer, Google Cloud, tip for startup is worth noting, "Build app that is powered by Gen AI than building GenAI itself" Also, big thanks to Soumik Ghosh, for leading such an engaging and impactful session. I really appreciate for the insights and energy you brought to the table! Conversive #GenAI #DataStrategy #AIInnovation https://lnkd.in/gNi_dAK3

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Thanks to Datanami for sharing my thoughts. Gen AI is amazing, and we are in the golden age of AI development. For AI to be adopted by the masses, we need a robust way to identify and mitigate risks. A lot of work is being done through the open-source community and leading tech providers around AI safety. With regulations coming in, there is optimism for a responsible AI future.

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TRIPLE BAM! If you missed it, here's the recording of our live Q/A with Jay Alammar and Joshua Starmer PhD! We talked about many AI topics, answered lots of great questions, and talked about two great books: Hands-On Large Language Models: Language Understanding and Generation, and The Illustrated Guide to Neural Networks and AI!!! https://lnkd.in/dcPHs7YQ

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Thanks Amir Bormand for a broad ranging discussion around AI, accuracy and how my academic training in neuroscience fits in! This was my first podcast... check it out and lmk what you think https://lnkd.in/gWKD-kdP

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We're launching the inaugural edition of Beyond Benchmarks, a deep dive into the metrics and trends observed across the early-stage enterprise cloud market. This is the first look at some of the business data around GenAI in SaaS. Some initial observations: 1) 60% of SaaS companies have already integrated GenAI into their offerings (60% of these as part of their current product and 40% as a new product), and an additional 20% are planning to do so this year. Almost half aren't monetizing these features. Those that are are primarily experimenting with both usage-based and flat fee pricing models. 2) Most companies are utilizing OpenAI as their primary LLM, but many are experimenting with multiple models - and we are noticing an early trend towards intelligently routing GenAI inference requests to different models based on cost, performance, and security. 3) Though we are in the initial innings of GenAI, we are seeing some positive signals - companies that implemented GenAI had 7% higher NDR than those that did not. Still early days, but we'll be doing this benchmarking report regularly to track and share how things progress in this new era. Link to report in comments.

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“AI’s “mirrors” look and sound a lot like us because they are reflecting their inputs and training data, with all of the biases and peculiarities that entails. And whereas other analogies for AI might convey a sense of living intelligence (think of the “stochastic parrot” of the widely cited 2021 paper), the “mirror” is more apt, says Vallor: AI isn’t sentient, just a flat, inert surface, captivating us with its fun-house illusions of depth.” the medium is the message, social networks the new medium and private networks the true repositories of value.

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Exceptional article by Walter Frick on the evolving views of economists about the impact of technology on workers, the workplace, and the economy. This is our world at KYield, Inc. -- my core patent for the KOS is optimizing knowledge yield in the digital workplace, first developed nearly three decades ago while operating the world's leading learning network for thought leaders. The name of the company is based on that theorem. Automation is necessary but woefully insufficient to achieve knowledge yield as knowledge is the domain of complex humans, even if LLM bots can mimic behavior. The more transfer of knowledge that occurs without permission, the less knowledge will be shared. One of the first lessons learned in knowledge transfer. Evidence has shown that when exploitation is excessive, false information will be transferred, as we've seen in the poisoning of LLM training data among many other case studies. Optimizing knowledge yield in the digital workplace requires a holistic systems approach based on deep understanding of several disciplines, hence the KOS (EAI OS) as the manifestation of the theorem. One of those disciplines is economics, where I've invested a good part of my career. I moderated the global economics community in our learning network (GWIN) in the late 90s, which included leading economists, and where I have conducted a fair amount of research myself. This work is mostly in the domain of behavioral economics, which is the subspecialty that best understands related phenomenon such as the influence of realized moral hazard in causing financial crises, and the wealth gap influence that can help trigger economic depressions. The land grab currently underway by LLM firms and Big Tech is actually quite similar to patterns in other industries that caused major catastrophes, such as the subprime mortgage disaster when a handful of "market makers" would have caused the collapse of the global economy if not for record levels of financial engineering by the Fed, which did severe damage to the U.S., and is still causing severe repercussions. One of many lessons in human-caused catastrophes is never allow specialists in one narrow discipline who have billions of USD at stake set the terms that impact everyone else. Surprising numbers of people have proven willing to throw society under the bus in an attempt to satisfy infinite greed or an ideological obsession. In the case of LLMs, not only do we have both greed and idealistic cults driving behavior, the implications include no less than risking the entire knowledge economy.

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Reid Hoffman collaborated on an intriguing book with ChatGPT, delving into how AI, particularly LLMs, can significantly enhance our abilities. In this publication, conversations with GPT4 explore diverse areas like creativity, education, and business, examining their advantages and disadvantages. For an audio experience, check out the Podcast version narrated by a text-to-speech engine trained on Reid's voice - well worth a listen. Well worth a listen/read if you want to expand your thinking to what can be possible with GenAI - https://lnkd.in/gHaDfvvE

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In our opening salvo for our book on the AI-Centered Enterprise, co-authored with Natarajan Balasubramanian and Amit Joshi, our editorial opinion article on "What Companies are Getting Wrong about AI" was published in TechTarget News. In this article, based on our research, we argue for a nuanced three phase approach to AI implementation in organizations. Arun Rao, my co-founder at samvid.ai, joins us as collaborator for this article. #enterpriseai #responsibleai https://lnkd.in/g3E4dx64

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I just bought a national subscription to American City Business Journals (ACBJ) so will be posting more articles from their network of 44 journals. The Puget Sound Business Journal was our primary source of regional business intelligence in the 1980s to early 90s, and it was instrumental for many younger growing companies, including Microsoft, Costco and Starbucks, among others. They are often the only pubs who cover important business news. When I filed my original core patent application in 2006, Google had 4 AI patents. In 2023, they had 1,870 AI patents. While there has been a massive spike in recent years due to the LLM hype-storm and Big Tech priority, what this really tells us is almost everyone was behind Google in AI -- and KYield frankly in our focus areas. It also tells us there is an LLM bubble. This article cautions on what occurred with the blockchain and the metaverse where there was a similar spike of investment and patents followed by a 70% bubble deflation. I expect that to occur in LLMs, but unlike the above mentioned -- AI has enormous value for consumers and businesses. We just need to plow the massive piles of noisy junk off the road so we can deliver the value. "Rather than obtaining patents with an eye toward suing competitors," Love said (Brian Love, Prof. of Law at Santa Clara University School of Law). "Silicon Valley companies tend to build portfolios for the purpose of deterring competitors from suing them." This is precisely our strategy at KYield. I decided not to pursue a portfolio of patent applications related to our Synthetic Genius Machine invention a couple of years ago for several reasons, including industrial espionage that ignores patent law (China is the leader but far from alone), the high costs associated with a complex IP portfolio, and other higher priorities. NM has some unique challenges in IP. Due to the national labs, there is plenty of IP, but there is precious little support for IP-related ventures as government dominates the economy, and government is an extremely poor early adopter. They not only have obstacles galore, they usually lack motivation or incentives. NM biz environment is primarily gov't contractors, mom & pops, a few mid-markets, & non-profits / quasi-gov't entities like healthcare and universities. The state VC fund is the only VC game in town of any size, and that's a political game. Otherwise, NM has a lot going for it... location, climate, affordability, science, infrastructure, but it is a challenged regional economy. There is no support like we experienced and provided in Seattle or SV. Even AZ offered a few options in the 90s. That said, there isn't any reason businesses can't thrive here -- it just requires a lot more energy and money to break through the early obstacles. We have quite a few now that are growing nicely. Several right here in Rio Rancho. Stay tuned.

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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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Here's why prompt engineering is one of today's most valuable skills. VentureBeat recently published an article by Deven Panchal of AT&T Labs. I applaud Deven for his vision. He says, "A well-crafted prompt can significantly impact the quality and relevance of the output of LLMs." So many are refusing to accept this. Mainly because prompting uses natural language. They are misguided, assuming AI can expertly prompt for them. Even if it can someday (which I doubt), it can’t today. The closest thing is SmartGPT 2.0, which still can’t compete with an expert prompt engineer. I recommend learning and practicing prompt engineering. 🟢 If you don't know where to learn, comment "START" and I'll point you in the right direction. --------------------------------------------- See comments for a link to the full article. 🔗 Follow 🔔Mark Fulton for more on #AI #Prompts #AIAgents

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𝐔.𝐒. 𝐋𝐞𝐚𝐝𝐬 𝐆𝐥𝐨𝐛𝐚𝐥 𝐀𝐈 𝐂𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧: 𝐀 𝐍𝐞𝐰 𝐄𝐫𝐚 𝐨𝐟 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 In a groundbreaking move, the 𝐔.𝐒. 𝐃𝐞𝐩𝐚𝐫𝐭𝐦𝐞𝐧𝐭 𝐨𝐟 𝐂𝐨𝐦𝐦𝐞𝐫𝐜𝐞 and the 𝐔.𝐒. 𝐃𝐞𝐩𝐚𝐫𝐭𝐦𝐞𝐧𝐭 𝐨𝐟 𝐒𝐭𝐚𝐭𝐞 have launched an international initiative to foster collaboration in 𝐀𝐈 𝐝𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐚𝐧𝐝 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞. This ambitious effort aims to establish a framework for global cooperation, setting the stage for a new era of AI innovation. At the heart of this initiative is the creation of 𝐠𝐥𝐨𝐛𝐚𝐥 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐬 𝐟𝐨𝐫 𝐀𝐈 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞. These standards emphasize 𝐭𝐫𝐚𝐧𝐬𝐩𝐚𝐫𝐞𝐧𝐜𝐲, 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲, 𝐚𝐧𝐝 𝐟𝐚𝐢𝐫𝐧𝐞𝐬𝐬, ensuring that AI systems are developed ethically and responsibly. By setting these principles, the U.S. aims to lead the charge in creating a trustworthy AI ecosystem. The economic and security benefits of this collaboration are immense. By driving innovation in AI technologies, the initiative is poised to boost economic growth. Moreover, it addresses critical security challenges, ensuring that AI systems are not only innovative but also 𝐬𝐞𝐜𝐮𝐫𝐞 𝐚𝐧𝐝 𝐫𝐞𝐬𝐢𝐥𝐢𝐞𝐧𝐭. This initiative opens up a world of opportunities for 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐞𝐬, 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐞𝐫𝐬, 𝐚𝐧𝐝 𝐩𝐨𝐥𝐢𝐜𝐲𝐦𝐚𝐤𝐞𝐫𝐬. It invites stakeholders to actively participate in shaping international AI policies and standards, ensuring that diverse voices contribute to the future of AI. Through this initiative, the U.S. reaffirms its commitment to being at the forefront of AI innovation, while prioritizing responsible and ethical development. This marks a significant step towards a collaborative and secure AI future. More details: https://lnkd.in/dCkThaSQ #AI #responsibleAI 𝘛𝘩𝘪𝘴 𝘱𝘰𝘴𝘵 𝘸𝘢𝘴 𝘸𝘳𝘪𝘵𝘵𝘦𝘯 𝘸𝘪𝘵𝘩 𝘵𝘩𝘦 𝘩𝘦𝘭𝘱 𝘰𝘧 3 𝘤𝘰𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘯𝘨 𝘔𝘪𝘤𝘳𝘰𝘴𝘰𝘧𝘵 𝘈𝘻𝘶𝘳𝘦 𝘖𝘱𝘦𝘯𝘈𝘐 𝘴𝘦𝘳𝘷𝘪𝘤𝘦 𝘢𝘨𝘦𝘯𝘵𝘴. 𝘈𝘐 𝘤𝘢𝘯 𝘮𝘢𝘬𝘦 𝘮𝘪𝘴𝘵𝘢𝘬𝘦𝘴, 𝘴𝘰 𝘱𝘭𝘦𝘢𝘴𝘦 𝘷𝘦𝘳𝘪𝘧𝘺 𝘵𝘩𝘦 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯 𝘣𝘦𝘧𝘰𝘳𝘦 𝘶𝘴𝘪𝘯𝘨 𝘪𝘵.

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When high-level individuals begin speaking publicly about social media harms, it signals one thing: there’s a clear market for Social Media Harm Reduction. While the Social Media Research Institute (SMRI) has yet to connect directly with these individuals in the UK mentioned below , plans are underway to establish a flagship presence there. This initiative aims to engage those interested in the field and provide university professors with opportunities to study and contribute to the development of Social Media Harm Reduction practices in the European Region. Which contributes to about $50 billion paid out because of social media related issues according to studies. Cc Declan Conway Social Media Harm Reduction ®️ Social Media First Aid ®️ https://lnkd.in/eBPcNqfT

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Solv's journey to $600 million GMV while maintaining profitability is a testament to the transformative power of technology in the MSME sector. By enabling market access and ensuring fair pricing, Solv is not just addressing pain points but also paving the way for economic empowerment and sustainability. The significance of this achievement cannot be overstated. MSMEs are the backbone of many economies, yet they often struggle with market access and pricing disparities. Solv's platform bridges this gap, leveraging technology to create a more equitable business environment. This is a powerful example of how innovative solutions can drive real-world impact. As tech professionals, entrepreneurs, and investors, we must ask ourselves: How can we contribute to this wave of change? Whether through investment, innovation, or advocacy, there are myriad ways to support the growth and sustainability of MSMEs. Read more about Solv's impact here: https://lnkd.in/gHUChyRB #MSMEs #TechForGood #Sustainability #EconomicEmpowerment #Innovation

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Watching Vinod Khosla talk with Rocky Yu about exponentials at the AGI House. Vinod said you could see the future of the Internet in the 1970s if you watched carefully. So, here are my guesses on what new fields AGI will revolutionize in what order: 1) Creative industries: image generation, music generation and movies 2) Robotics: foundational models will enable much better robotics to be deployed much more widely 3) Biotech: the creation of new drugs, better therapies etc…

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AI continued to dominate conversations at KubeCon+CloudNativeCon, according to Shaun O'Meara, CTO of Mirantis. Reflecting on the event in Salt Lake City, Utah, O'Meara emphasized the widespread interest in AI among attendees, journalists, and analysts. Key discussions centered on the challenges and strategies for running AI workloads on infrastructure and navigating the intersection of these technologies. #KubeCon Cloud Native Computing Foundation (CNCF) #Ai #GenAI #OpenSource

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