Indy Sawhney

Great article from the superstar Harvard Business School team led by Karim Lakhani on how Generative AI is reshaping cultures and ways of working by lowering the expertise threshold in large organizations! This article is based on a multiple recent studies and both confirms trends we've seen before and reveals hidden patterns that every Leadership team should pay attention to. Here are my key take-aways: Confirmed Trends - Efficiency: Individuals using AI significantly cut down task time and teams matched or exceeded performance vs. control group without AI, especially in cross-functional tasks. - Efficacy: Teams with AI produced top-quality solutions at a higher rate than other groups, showing that human collaboration combined with AI generates increased performance. - Business Integration: AI usage enabled participants to develop solutions outside their expertise, e.g. technical and commercial. AI can help break down silos with broader problem-solving across functions. Hidden patterns - Team dynamics: AI usage reshapes teamwork by flattening hierarchy, especially in knowledge intensive teams as it helps balance contributions from team members with varying degrees of expertise. - Emotional Impact: AI users reported increased positive emotions (excitement, energy) and reduced negative ones (anxiety, frustration). This indicates that AI can significantly enhance the work experience. - Cognitive Dissonance: Despite objectively better performance, AI-assisted participants had lower confidence in their outcomes, revealing a disconnect between reality and perception in AI-augmented work. This is the only clear negative outcome of the study. Potential causes may be culture related, and we should stay ahead with learning and communication: 1. Less effort is tied to lesser outcomes, in spite of precedents such as industrial automation, computing, etc. 2. Work done with AI is (still) felt as "cheating", and therefore taints the experience as a fraud, undermining confidence 3. The outcome feels less personal and relatable. This could be a good thing too if it leads to more fact-based discussions in decision making vs. strong attachment to one's own ideas and preconceptions. As culture influencers and leaders, our focus should be on how we can start shifting the cultural norm regarding AI augmented work. This reminds me of online dating in the early 2000's! 🙄 Time to move on... https://lnkd.in/eyG6zCQk

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This California Management Review article explores the ROI of AI ethics and governance investments through two lenses: loss aversion and value generation. While many companies focus on minimizing risks like legal penalties and reputational harm, the article argues that a value generation approach—using ethics to build trust, foster innovation, and create competitive advantages—offers greater long-term benefits. By integrating ethics into strategic planning, organizations can both mitigate risks and enhance overall growth.

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💡 Exploring How Explainable AI Could Revolutionize Drug Discovery 💊\ Imagine AI not just predicting which molecules might become new drugs, but also explaining why it thinks so. This transparency is what makes XAI so exciting—it’s like having AI pull back the curtain and show its reasoning process. In the article, researchers, discuss how they’re using XAI to better understand AI models that predict new antibiotics. XAI revealing some crucial insights that could lead to more effective drugs and a stronger defense against antibiotic resistance. #AI #DrugDiscovery #ExplainableAI #Innovation #HealthTech #Antibiotics #FutureOfMedicine 🚀

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Researchers at the Flatiron Institute's Center for Computational Neuroscience have developed a new model of neurons that significantly enhances artificial neural networks by allowing neurons to act as controllers, influencing their environments based on gathered information. This advanced model could lead to more effective and efficient AI systems, mimicking more closely the complex capabilities of human brains. #Science #Technology #AI #NeuralNetworks #AIResearch #BrainScience #ComputationalNeuroscience #TechInnovation #Innovation How do you think this new model of neurons as controllers might impact the future development of AI technologies in fields like healthcare and autonomous driving? https://lnkd.in/g3ZDKT7T

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As we confront today’s online harms, we must prepare for the next frontier: an embodied, immersive internet powered by #AI, #biotech, #decentralization, and #quantum #computing. While tech companies distract us with superficial features and short-term solutions, they remain opaque about their true vision for our digital future—one that will fundamentally reshape human experience, society and childhood. As we vitally address the online harms of today, my focus is on the next iteration of the internet—the embodied internet, a transformative evolution fueled by #quantumcomputing, #AI, #biotech, and #decentralization. These technologies are converging to create a digital landscape that is more immersive, personalized, interconnected and powerful than ever before. 🔆 AI is driving unprecedented advancements in how we interact with technology, enabling systems to adapt and respond to human behavior in real time. 🔆 Biotech is blurring the lines between the physical and digital, opening possibilities for human augmentation and new forms of interaction. 🔆 Decentralization is reshaping power structures, offering the potential for greater equity and autonomy in digital spaces, but also raising questions about governance and accountability. 🔆 Quantum computing is unlocking new possibilities in data processing, encryption, and simulation, providing the computational power needed to support these transformative technologies. As we move towards an internet enhanced with #spatialcomputing, where digital experiences become increasingly embodied and integrated into our physical world, we must prioritize the development of frameworks that protect and empower users. I'm committed to fostering these conversations and helping shape a future where innovation and responsibility go hand in hand. . 📚 Essential reading for understanding this future: "The Age of Surveillance Capitalism" by Shoshana Zuboff "Life 3.0: Being Human in the Age of Artificial Intelligence" by Max Tegmark "Reality+" by David Chalmers For more on my work and insights: www.ninajanepatel.com 📸 NBC News #CuriosityShapesTomorrow #SpatialComputing #EmbodiedInternet #DigitalSafety #EmergingTech #AI #Biotech #Decentralization

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Gemini Advanced rolls out ‘Deep Research’ as first agentic feature [U] https://lnkd.in/g6kKGwHy I tried the next thing... it's definitely worth using especially if you have a deep level of professional expertise and information technology or other areas. As you start exploring it explore areas that you know well to see how well the benchmarks against your experience and then think about what it's able to achieve to automate parts of your practice or parts of your program. After that start exploring areas that you don't know about to see if this kind of construct can help you in learning things faster or going deeper in your practices and programs. #ai #education

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One of the most fascinating discussions you can watch on what #AI can do for science. It really does make you dream https://lnkd.in/eGBf9qGF

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In conjunction with Biden’s AI Executive Order from last fall, the President's Council of Advisors on Science and Technology (PCAST) just released a study and report exploring the implications of AI for scientific research. A key focus is on how a well-designed, equitably shared, and responsibly used data and AI infrastructure could empower scientists and others to tackle some of our greatest societal and global challenges. Executive summary is below.  Special thanks to Eric Horvitz, Chief Scientific Officer at Microsoft for his work on this committee. #ai #responsibleAI #aiinresearch

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Will AI Replace Me? 🤔 One moment you're cruising, feeling irreplaceable, and the next you're wondering if a robot just outperformed you. This video sums it up perfectly - Check it out: https://lnkd.in/d-cwjxj6 AI isn’t here to replace you. It’s here to replace tasks, not creativity, emotional intelligence, or adaptability. The key is learning to work with it, not against it. #AIandJobs #CareerRollercoaster #FutureOfWork

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In case you missed it.... We published a great H:F guest episode with Joel Portice, CEO of egnite - delving into the transformative role of data and AI in revolutionizing cardiovascular care. Joel shares his journey of leading five successful healthcare data companies, including the genesis and rapid growth of egnite, which was spun out from Edwards Life Sciences. egnite's flagship platform, Cardio Care, uses advanced analytics, machine learning, and AI to identify and manage cardiovascular patients, saving lives daily. This episode is a strong addition to our Heart Health Series on Health:Further. Please check it out: https://bit.ly/4fKmzCH

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The advancements in AI and data integration within the pharma industry are truly groundbreaking. Steve Nouri's post on this seismic shift in drug discovery highlights how the integration of AI and data is set to revolutionize the field. NVIDIA CEO Jensen Huang’s insights were particularly enlightening. The idea that AI can simulate complex biological interactions, much like it does with 3-D graphics, is a game-changer. This new approach, dubbed TechBio, uses connected datasets to train AI models, making drug discovery a more efficient and accurate process. It's incredibly exciting to witness these advancements. For the first time, we have the potential to speed up health discoveries and truly start curing the incurable. The future of AI in pharma is bright, and I’m thrilled to be part of this transformative journey. #AI #TechBio #Innovation #Pharma #DrugDiscovery #Healthcare

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The integration of large language models (LLMs) in healthcare shows promise but also raises critical questions. While LLMs offer potential benefits such as improved diagnostics and patient care, challenges like data privacy and bias remain. Stanford's report examines the current landscape, highlighting advancements and emphasizing the need for cautious implementation. As LLMs evolve, addressing ethical and technical concerns becomes imperative to realize their full potential in healthcare. https://lnkd.in/g9SkQieH

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5 questions with Marcello Cacciato (Metyis) on bringing Generative AI to life Marcello Cacciato, Director in the Data Science practice of Metyis, is an expert Generative AI, having advised multiple organisations on the development and implementation of their Generative AI stra https://lnkd.in/efSSGj3g to-life

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Struggling to Demonstrate ROI with GenAI? Here’s a Game-Changing Insight If you're finding it challenging to showcase the ROI of Generative AI, the key lies in selecting high-impact use cases. A great example comes from Genentech and NVIDIA, who are leveraging GenAI to revolutionize drug discovery in Early Development and Research. In this short video, they demonstrate how GenAI is being used to design novel molecules and generate experimental data, aiming to uncover the next big breakthrough in medicine. These advancements not only accelerate the drug discovery process but also hold the potential to transform healthcare as we know it. This is innovation at its finest, paving the way for a healthier future for all. https://lnkd.in/eG5aBadw

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5 Real Scenario to Prove “When data meets research, innovation begins" https://lnkd.in/geuyPWNM #DataInnovation #ResearchAndData #DataDriven #InnovationStartsWithData #RealScenarios #complereinfosystem

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Large language models-- or #LLMs --are a type of generative pretrained transformer (GPT) that can create human-like text and code. There's a lot of talk about GPTs and LLMs lately, but they've actually been around for years! In this video, Martin Keen briefly explains what a LLM is, how they relate to foundation models, and then covers how they work and how they can be used to address various business problems.

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🚀 I recently had the honor of delivering the keynote address at WOCIP's Generative AI Symposium. The event was filled with amazing panel discussions and a thought-provoking session by Erin R., founder of #ChatBlackGPT. In my keynote, titled "𝗧𝗿𝗮𝗶𝗹𝗯𝗹𝗮𝘇𝗶𝗻𝗴 𝗶𝗻 𝗮 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗪𝗼𝗿𝗹𝗱," I focused on five guiding themes that I believe are essential for navigating this rapidly evolving field. I chose these themes because they encapsulate the mindset and actions necessary to not just adapt to change but to lead it. 1. 𝗖𝗵𝗮𝗻𝗴𝗲: Embrace it; don't wait for it. In a world of constant evolution, staying comfortable means staying behind. I highlighted this theme to encourage us all to be proactive and ready to pivot, recognizing that change is the only constant. 2. 𝗖𝘂𝗿𝗶𝗼𝘀𝗶𝘁𝘆: Obsess over learning. Curiosity isn't just a trait—it's a pathway to innovation. I believe that by diving deep, questioning everything, and constantly seeking ways to create value, we can unlock new possibilities. 3. 𝗔𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆: As we explore generative AI, it's our responsibility to build and deploy it thoughtfully. I emphasized this theme to remind us to consider who we're designing for, assess potential impacts, and remain vigilant about risks and biases. 4. 𝗔𝗰𝘁𝗶𝗼𝗻: Move beyond theory. Start experimenting, get hands-on, and integrate AI into your daily activities. I chose this theme because real progress comes from doing, not just thinking. Remember, AI won't replace you, but those who harness it will drive tomorrow's world. As noted by Adobe's Eric Hall, "𝗔𝗜 𝗶𝘀 𝗻𝗼𝘁 𝗴𝗼𝗶𝗻𝗴 𝘁𝗼 𝗿𝗲𝗽𝗹𝗮𝗰𝗲 𝗽𝗲𝗼𝗽𝗹𝗲, 𝗯𝘂𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗮𝘁 𝘂𝘀𝗲 𝗔𝗜 𝗺𝗮𝘆 𝗯𝗲 𝗿𝗲𝗽𝗹𝗮𝗰𝗶𝗻𝗴 𝘁𝗵𝗲 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗮𝘁 𝗱𝗼𝗻'𝘁 𝘂𝘀𝗲 𝗔𝗜." 5. 𝗖𝗵𝗼𝗶𝗰𝗲: At the end of the day, we have a choice. The tools are right here. I included this theme to empower each of us to embrace these opportunities and redefine what's possible—or risk letting them pass us by. The demand for AI expertise is surging. Job postings requiring AI skills have increased by 𝟭𝟵𝟬%, reflecting the growing need for professionals proficient in AI technologies. [Source](https://lnkd.in/e47ac5t7) Moreover, sectors more exposed to AI are experiencing almost 𝗳𝗶𝘃𝗲 𝘁𝗶𝗺𝗲𝘀 𝗵𝗶𝗴𝗵𝗲𝗿 𝗴𝗿𝗼𝘄𝘁𝗵 𝗶𝗻 𝗹𝗮𝗯𝗼𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆, indicating the transformative impact of AI adoption. [Source](https://lnkd.in/e_BkjJx8) Here's to harnessing the power of generative AI to accelerate time to value, especially for patients and people in need. Kudos to Angelique Hopkins PhD, MPH and Latrice Abanyie for co-chairing this phenomenal event. #𝗪𝗢𝗖𝗜𝗣 #𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲𝗔𝗜 #𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 #𝗟𝗲𝗮𝗱𝗲𝗿𝘀𝗵𝗶𝗽 #𝗔𝗜𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 #𝗙𝘂𝘁𝘂𝗿𝗲𝗢𝗳𝗪𝗼𝗿𝗸 #𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻

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#NVIDIA & #OCI have a solution to help enterprises leverage their structured and unstructured data more effectively, enhancing both the quality and reliability of #generativeAI outputs using RAG (Retrieval-augmented generation) pipelines. The vast majority of the world’s data remains untapped, and enterprises are looking to generate value from this data by creating the next wave of generative AI applications that will make a transformative business impact. RAG pipelines are a key part of this, enabling users to have conversations with large corpuses of data and turning manuals, policy documents, and more into interactive generative AI applications. #clinicaldata #oracle https://lnkd.in/gvaCNTb2

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Just 2% of enterprises in the U.S. and U.K. actually have deployed AI solutions Another provocative article from Forbes CIO, both on their premise and callout of the fundamental challenge which is routinely overlooked: it's all about the data   All the talk about AI and everything it can do for businesses may make it feel like most companies are already using the technology, but a new study from K2view shows that isn’t necessarily the case. The data preparation company found that as of July, just 2% of enterprises in the U.S. and U.K. actually have deployed AI solutions. What’s the holdup for everyone else? Other than cost, it’s issues dealing with data. The problems that enterprises have with their data are myriad. Nearly half say they are concerned with data security and privacy in a generative AI system. And a third of all companies are still working on data readiness—a top issue for 45% of all companies with 5,000 or more employees. The data issues also cover many areas. A total of 48% of companies see problems with scalability and performance. Issues with quality and consistency, as well as real-time data integration and access challenges are major difficulties for 46% of respondents. Companies identified many valuable internal data sources for potential customer-facing AI integrations, meaning there are a variety of different databases and data types to sync up. Customer interactions—which can run the gamut from invoices to emails to chats with a helpdesk—are valuable to 56% of companies. But almost as many see CRM customer data and marketing data as key. Financial data, which is likely to be more standardized than some of these other types of information, is in a distant fourth place, with 36% of users seeing it as a top source for AI. These results illustrate a common issue many companies are trying to deal with when transitioning to AI. Data is only useful when it can be accessed, its information recognized and “understood” by the AI system, and the information can be used to determine a customized outcome. Though most businesses have data dating back to when they first started using computers, it can take a lot of effort to make it useful. But while data prep work may end up being just as taxing as programming generative AI applications, studies have shown that the efficiency of an AI system may be worth the effort. #AI #CorporateData #Strategy #ForbesCIO

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