Pradeep Chelpati

The work that Anthropic is doing to unravel the black-box nature of #LLMs is brilliant, foundational, and highly commendable. They are addressing a key challenge in any neural network -- explainability. Not only can this research lead to safer and more-accurate models, but the ability to explain WHY a model generated a specific response is critical in many regulated industries. Bravo!

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As enterprises grapple with AI strategy and emerging regulatory pressure, high-performing companies are establishing cross-functional AI councils to align AI use with enterprise strategy, values, and regulatory requirements. Recently one of our healthcare clients was approached to participate in a research partnership to build out a disease specific large language model - thanks to the establish risk management practices, they were able to ask the right questions and implement appropriate guardrails. In my most recent Forbes Technology Council article, I share: • Key roles to include on an AI council (hint: it's more than just tech experts) • Core responsibilities and deliverables • Real-world examples of successful AI councils • Common pitfalls to avoid and how to overcome them Whether you're just starting your AI journey or looking to level up your governance, AI councils are critical for staying competitive while mitigating risks. With incoming regulations like the EU AI Act, having a strong AI governance structure is no longer optional. Check out the full article below to learn how to build a successful AI council for your organization 👇 #AI #AIGovernance #ResponsibleAI #Innovation

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Navigating the journey from pilot projects to scalable production in #GenAI is filled with challenges and will require a strategic and disciplined approach. A rough estimate is that only 10% of the pilot projects scale in large enterprises. Focus needs to be on business value, establishing a standard GenAI #platform, change management, and cost management. A recent #McKinsey article talks about steps required to scale. I appreciate the article's emphasis on the need for a GenAI platform that integrates within the enterprise tech stack. It's not just about #LLMs. More focus is needed on such architecture and evolving patterns. The tech stack illustration effectively highlights how various capabilities – like orchestration, semantic search, data extraction, guardrails, and prompt engineering - come together to create a robust GenAI solution. The future expansion of the agentic workflow will further enhance this architecture. Link to the article in comments.

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How can #blockchain transform healthcare data management? Abderahman Rejeb, Mike G., Anjum Khurshid, Alex Norta, Jim Poteet, Suresh Sivagnanam and I believe that the changes will be #disruptive and profound. In our newest publication in Blockchain in Healthcare Today - DMV Chapter, we identify important areas related to current #challenges, #stakeholders, #legal environment, #trust and #privacy, #benefits, #data #integrity, data #security, data #interoperability, data #sharing and #transfer as well as numerous #future #developments. This paper should not only help #researchers to identify interesting areas but is also relevant for #practitioners to better understand the potentials of blockchain for the #healthcare #industry. The open access paper can be found here: https://lnkd.in/dBrgqJ7r This paper is based on a #panel #discussion that can be watched here: https://lnkd.in/dQamzKNp We hope that we can raise awareness and contribute to a more efficient #healthcaresystem that will benefit #patients and the #industry. Many thanks to John Russo and Tory Cenaj for their ongoing support.

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#PendlerPod Natural language models are the future. For successful AI adoption, a dedicated internal change manager should oversee implementation, as an external hire may face integration delays and cultural barriers. Agility is key; companies must adapt to new technologies and ensure processes are future-proof. Maintaining a human-in-the-loop approach for critical decisions ensures AI complements human judgment. Zack Kass visits Inspari’s #Dataklubben with pod hosts Heino Lærke Vigsø and Rosa Ryberg. #transformation

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The hunt for a pool of data scientists might be holding your digital transformation back. A new breed of leader is emerging: the AI Enabler. Here’s what you need to know about building your own class of AI Enablers: http://spklr.io/6040qSon #AI #GenAI #DigitalTransformation

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The Analytics India Magazine has a piece on an Indian startup "building a private Perplexity for enterprise" https://lnkd.in/ec-_xt8x. #generativeai #perplexity #startup #artificialingelligence #startup #perplexity #analyticsindiamagazine

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🧠 Board's effective AI Oversight in Business Transformation 🧠 Board's Effective AI oversight will define the success of digital and AI-led business transformation for the new tomorrow. Board Chairs, Lead Directors, Board Directors, are you ready to engage and oversee the C-Suite? Boards must treat AI as strategic and integrate it with business strategies. This is a team sport – Chief Risk Officers, CISOs and Chief Privacy Officers should have a seat at the table to manage privacy and security imperatives around transparency and Zero Trust Architecture. Learn more here from my LinkedIn piece (https://shorturl.at/gbiyK) . Key Focus Areas: ✅ Oversee Quantitative Metrics for security and business outcomes ✅ Engage and Oversee Capital Allocation Decisions to avoid long-term value erosion ✅ Oversee Qualitative Metrics associated with Open Innovation, Developer & Employee Experience through AI-led initiatives ✅ Engage and Oversee Quantitative Metrics associated with New Revenues from product-led growth and customer experience infused Earnings Growth Rate Value Plays ✅ Engage and Oversee Control Effectiveness, data resilience, and AI Ethics Maturity Models. Per The Wall Street Journal, Goldman Sachs will roll out its first generative AI tool for code generation to thousands of developers by the end of the month. Marco Argenti has a great start here from the CIO lens. 🔍 What metrics are you tracking to ensure AI success in your organization? Kanika Saraiya Havelia Manuj Aggarwal Christopher Hetner Angela Yochem Lidia Fonseca Peter High #CEO #KSgems #AIoversight #TechStrategy #OperatingModel #EBITDA #CIO #CTO #CISO #BoardGovernance #AI #BusinessTransformation #Leadership https://lnkd.in/etV_Bp2D

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Clear your afternoon schedules, folks! Today Dataiku and NVIDIA are showcasing the latest advancements in accelerating #AIinHealthcare, and you don't want to miss it! Stay ahead of the curve and join us to learn more. #healthtech #datascience #innovation https://lnkd.in/eFXNyfaD

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📢 NVIDIA aims to boost #developerproductivity with NIM (Nvidia Inference Microservices). ✔ Provides a simple and standardized way to add Generative AI to applications ✔ Provides models as optimized containers pre-built to speed model deployment for GPU-accelerated inference ✔ 40+ community models available incl Google’s open model Gemma, Meta's Llama 3, Microsoft's Phi-3, Snowflake's Arctic ✔ Allows enterprises to efficiently use infrastructure - bye, bye unnecessary infra costs #mindfulCIO #GenAI #AI 🍒 Share your thoughts in the comments. 👇 🍒 Like and share this post with your followers. 💓 🔗 See comments for the link

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Interesting thoughts from Junta N. about #AI use cases in #insurance.

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In today's data-driven world, #healthcare and #life sciences (HCLS) organizations are facing an unprecedented surge in #data #volume and #complexity. To harness this data effectively and gain a #competitive edge, establishing a robust Center of Excellence (CoE) for #Data & #Analytics is becoming increasingly crucial. Last 12 months I interacted with over 15 CIO/CTO from HCLS building their CoE for D&A ! Working closely with them helped me put some thoughts together for companies looking to start on this journey. Imagine a world where: ➡️ Data-driven decision making enhanced customer experience, risk management, and product development. ➡️ Streamlined operations through data automation and optimized workflows lead to significant efficiency gains. ➡️ Reduced costs by minimizing data redundancy, optimizing resource allocation, and potentially reducing reliance on external data analysis services. But where do you start? How do you build a centralized hub to turn insights into action? A well-structured Data & Analytics CoE can make this vision a reality. A successful #CoE implementation requires a collaborative approach. Working closely with your #HCLS organization to understand specific needs, define CoE goals, and establish a clear roadmap for success. ➡️ It's a marathon, not a sprint - 82% of healthcare orgs may have analytics initiatives, but many lack a cohesive CoE approach. Don't get discouraged by complexity. Start small, focus on early wins. ➡️ The "why" matters most - Don't build a CoE just because it's trendy. Find a burning pain point – better patient outcomes, streamlined costs, etc. – to rally stakeholders around. ➡️ It's a team sport - Doctors, data scientists, IT – a successful CoE breaks down silos. Get buy-in early, make everyone feel like co-creators. The Data & Analytics CoE - A Strategic Framework Aligned with Best Practices I recommend a structured approach to CoE establishment. Here's a framework to consider; ➡️ Key Teams and Roles 📍Data Governance Council: Senior leaders who set the strategic direction for data. 📍Data Management Team: Ensures data quality, security, and accessibility. 📍Analytics Team: Data scientists, analysts, and business intelligence specialists who develop models, analyze data, and generate insights. 📍CoE Leader: An experienced data professional who oversees the CoE's operations and alignment with business goals. ➡️ Key Functions 📍Data #Governance: Establish policies and procedures to ensure data quality, consistency, and accessibility. 📍Data #Architecture and #Infrastructure: Design a scalable and secure data architecture to support the CoE's needs. 📍Data #Skills Development: Build data literacy and analytical skills across the organization through training programs. Where are you in this journey & what are some key challenges you have faced ? Comment below 👇🏽Teqfocus Jas Kaur Aditya Arora

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#genai #largelanguagemodels #usecases that I'm looking forward to beyond creative use cases. Major assumption is #referencing hallucinations have been permanently solved. Also, naively, that society would want these changes versus more #augmented #deepfake videos and #entertainment. ✅ #education especially the effort needed to perform #literaturereview. Literature reviews are essential to identify that any new #phd research doesn't repeat preexisting work. Secondly to navigate from the original research source, how the topic has evolved and branched out to its many fronds or specific #hypothesis testing and validation. There's been software to help with the traceability, but producing a write up that defends the research and why it fills a gap and its usefulness is quite an arduous effort. The hope is #genai can accelerate the process thus allowing researchers to focus on hypothesis testing versus justifying why it's needed in the first place. Moving forward, potentially even uncovering gaps still needing testing! Universities will potentially see a renaissance! ✅ #legal and other forms of #contract interpretation particularly summarisation of key points, and eventually detection of conflicting statements (I say eventually because the tech hasn't reached this stage as yet once you know how it works). The idea is simplification of precedence, abstraction of principles and juxtaposition to context and emergent scenarios. The goal is swift justice sans unfairness between the rich and powerful versus the poor that are ill represented. Crucially, a transformation of #judiciary expediency. ✅ #information authenticity and validation I dramatically call the #ai phase of humanity as the #ageoflies. #ai created videos will not suffer from #uncannyvalley, the providers will fix the awkward 7 fingered #aigenerarted actor with strabismus (cross eye). As such #politics will insist on these tools to create #misinformation. While regulations will be enacted, history has shown how rapidly criminal activities proliferate before there's sufficient resources available to stop it. The hope is that the major providers will not only #probono, but set aside investments to detect whether a news/socialmedia #audio or #video clip is #authentic or #fake. Without which, I'm concerned the "Age of Lies", as dramatic as it sound, will splinter society far worse than it is today. As people will default to believe solely based on dogma and devolve into ignoring data, as content can no longer be trusted... ...hmm, sounds like a sci-fi plot https://lnkd.in/gWjv9APg

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#Technology like history tend to repeat itself. #Llama is doing an #opensource like what #redhat did decades ago. There's many nuances though ✅ #meta is a giant compared to #redhat ✅ unlike an #os that can run on any low cost #pc hardware, these #genai models require hundreds to thousands of super expensive specialized #gpu to produce outcomes. heck, even #gpu is a misnomer as the tech evolves, they'll be specific hardware for each of the major providers (#openai, #google) just like #crypto #mining cards. ✅ it'll be a large #corporate and #government play as a vendor because smallco won't be able to afford training their own models and owning those cards to optimize #training ✅ They'll be secondary market play via specialist smaller #ai companies that ride on the #platforms and existing models provided by #microsoft and others. in which they then offer services to smaller companies. ✅ what is still in immaturity, is building the #genai #usecase. While creative outputs like videos and drawings are entertaining, outputs that are beneficial to the world are still rare. I'll share in a different post what I'm looking forward to.

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🚀 Transforming Data Strategy for the Future: The Rise of Data Mesh and Composable Architecture 🚀 🔗 Dive into our latest feature at The CDO TIMES: "The Evolution of Organizational Data Ecosystems" – a comprehensive look at the seismic shifts in data management paradigms from traditional, rigid frameworks to dynamic, integrated digital ecosystems. 🌐 In this era of rapid digital transformation, understanding the strategic implementation of Data Mesh and Composable Data Architecture is not just advantageous—it's essential for staying ahead. These architectures aren't just about managing data; they're about empowering businesses with flexibility, agility, and the capability to innovate faster than ever. 💡 Key Insights: Data Mesh decentralizes data management, turning data into a product that drives business efficiency and innovation. Composable Data Architecture offers the flexibility needed in today’s fast-paced market, allowing businesses to adapt swiftly and efficiently to changing data needs. 🔍 We're at a pivotal moment where data isn't just part of the business; it is the business. As we move towards more advanced integrations of AI and potentially quantum computing, the stakes will only get higher. 📊 Whether you're a C-level executive strategizing for the next big shift or a data professional looking to stay on the cutting edge, this article provides essential insights and strategic frameworks that will help chart the course of your organization’s data future. 👉 Read the full article and join the conversation about how these revolutionary data frameworks are shaping the future of business. https://lnkd.in/eAkacPfp #DataStrategy #DigitalTransformation #DataMesh #ComposableArchitecture #BusinessIntelligence #CDO #Innovation #AI #QuantumComputing #TheCDOTimes

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Just wrote a blog on choosing the right data architecture for your complex data ecosystem, the evolution of data architecture over years and structuring data architecture teams to be the most effective for each of these options. As always, comments will be highly appreciated. Happy 4th of July! https://lnkd.in/ejrKX7qW

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