Machine Learning Week

A surprisingly easy way to multiply an AI model’s profit is to drive decisions via expected value instead of predictive scores. Here's how, illustrated with fraud detection. Read Eric Siegel's latest in Forbes: https://lnkd.in/gKGfcG9a

The great potential of LLMs is significantly compromised by their Achilles heel: a deadly reliability problem. Predictive AI can address this problem – and that represents the next killer app for predictive AI. Enterprises such as Instacart, HP, Salesforce and Twilio are now adopting this inevitable, crucial pivot. Here’s the late breaking news on this movement. Even as agentic AI hype overpromises, it serves to illuminate a prevailing goal, the enterprise’s inherent desire to press the limits of LLM-based autonomy. Companies want to deploy AI systems that perform roles rather than only tasks. They want machine “agency,” not only tools. (Of course they do; automation is the point of any machine.) But AI hype has everyone tied up in knots. It cultivates internal tension: On one hand, you suffer from intense fear-of-missing-out (FOMO). On the other hand, you don’t want to fall for infeasible or ludicrous claims. It’s easy as hell to think up an unrealistic goal for AI. And it’s almost as easy to work up a prototype, an impressive demo that just doesn’t scale. LLMs are so seemingly humanlike, people envision computers replacing all customer service agents, summarizing or answering questions about a collection of thousands of documents, taking on the wholesale role of a data scientist or even making a company’s executive decisions. Even systems meant to achieve more modest "agentic" goals quickly become too unreliable to deploy at scale. For example, in a recent study conducted by AI startup Mercor, the very best of several competing LLM-based systems, Gemini 3 Flash, succeeded at only 24% of a testbed of tasks, such as: “Reply back to me with the P/E ratio for KVUE, rounded to two decimal points. Use the implied share price in the Discounted Cash Flow model and diluted EPS from the annual financials dated 12/23/2025.” Good news: Hybrid AI can realize a good portion of AI’s often-audacious promise of autonomy. Predictive AI serves as a reliability layer that hands over to a human the cases and interactions most likely to go off the rails... Read the full article, Eric Siegel's latest in Forbes: https://lnkd.in/gm4TWvK5

ML Week's HYBRID AI 2026 kicks off next week in San Francisco! Therefore, this week is your last chance to register with pre-event pricing. Check out the detailed event agenda to learn why genAI needs predictive AI – and vice versa – and see a variety of other ways in which hybridizing methodologies delivers value. https://lnkd.in/gfDsspDR

It's finally here! ML Week's HYBRID AI 2026 takes place next week in San Francisco. Click below for details on speakers hitting the stage to cover: - Operationalizing Knowledge: A Practical Path to Neurosymbolic AI - Stress-Testing AI: How CSAA Built an Independent Model Validation Function to Catch Risk Before It Reaches Production - Validating External Data at Scale: a Solution to the Latest Challenges ... and many more, including speakers from HP, Netflix, DoorDash, Amazon, Spotify, OpenAI, JP Morgan Chase, Capital One, American Express, CVS, Microsoft, Discover Financial Services, Salesforce, and State Farm. https://lnkd.in/geKHKFQM

ML Week's HYBRID AI 2026 is coming right up: San Francisco in two weeks! This includes keynotes from OpenAI, State Farm, IBM, and Alphabet X’s moonshot factory. These keynotes cover: - Context engineering: how machines remember and forget - Generative Architecture - The organizational requirements for AI transformation - Blending LLMs with enterprise ML Plus, the event founding chair Eric Siegel will open with a keynote about how predictive AI serves as a much-needed reliability layer for genAI; this represents the latest killer app for predictive AI. Check out the detailed keynote descriptions and the overall conference agenda here: https://lnkd.in/gpuM8Scn

Check out the details of these sessions from Netflix, Salesforce, and AAA – coming to ML Week's HYRBID AI 2026, May 5-6 in San Francisco. The sessions cover: NETFLIX: Modern generative AI systems—from LLMs to multimodal models—are no longer compute-bound; they are memory-bound.... SALESFORCE: As enterprises rapidly adopt AI agents, a critical risk emerges: misconfigured or compromised agents performing anomalous, potentially harmful, data operations... CSAA INSURANCE (AAA): As organizations scale their use of machine learning and generative AI, the cost of model failure grows... Click below for more detail, and access the entire event agenda: https://lnkd.in/g3XFPBxr

“AI is coming for tasks, not for titles!” https://lnkd.in/gzWMjcbe

Predictive AI just took a leap forward. FeatureByte – a Gooder AI strategic partner – has advanced the state-of-the-art for predictive AI model development. Its groundbreaking approach supercharges the discovery of predictive features within your data by leveraging the power of LLMs. Your predictive models just got a whole lot better. But what's the true value of a better model? What does improved prediction deliver – in business terms such as profit, cost savings, returns, or other KPIs? To answer this question – and ensure that better tech means more value – FeatureByte and Gooder AI have partnered to offer a focused professional-services engagement called Model Reality Check. https://lnkd.in/gkUHiEgb

To achieve the AI value everyone talks about but few realize, you need to adopt HYBRID AI. Conference founder Eric Siegel has been writing and keynoting on the topic a lot over the last couple years, and this year's chapter of ML Week – HYRBID AI 2026, May 5-6 in San Francisco – is packed with enterprises walking the walk and talking the talk. Hybrid is in play. Come learn how to adopt it. https://lnkd.in/g9Mhx4KC

Eric Siegel is presenting twice at HYBRID AI 2026, this year's edition of Machine Learning Week – May 5-6 in San Francisco: A KEYNOTE PRESENTATION: Predictive AI’s New Killer App: GenAI’s Reliability Layer A TALK ON ML VALUATION: Profit, Not AUC! Using Gooder AI to Maximize Predictive AI’s Value Check out the details here: https://lnkd.in/gqrt4hmH