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Nice Article on Andrej and DCM!
Nice Article on Andrej and DCM!
Can you tell me about Data Capital Management? DCM is the new generation asset management company, disrupting the…
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Michael Beal shared thisMichael Beal shared thisHope everyone had an awesome Thanksgiving! Now on to #ReInvent! Join Bloomberg's Global Head of Enterprise Data Content Leila Sadiq and Co-Head of Enterprise Data Science Specialists Michael Beal at the Snowflake Booth at #AWSReInvent to learn how to accelerate time to value with Bloomberg's data on Snowflake! This Lightning Talk will explore how Bloomberg Data License helps customers deal with evolving complexity and accelerates their journey to the #cloud. Michael will showcase two innovative AI-driven customer use cases incorporating a vast array of traditional and alternative #data including fund flows, supply chain, security ownership, geopolitical and supply chain risk, ESG, regulatory considerations and more. Mark your calendars: Tue, Dec 3, 11:30am at the Snowflake Booth #714 in the Venetian Expo! Find all Snowflake sessions at Re:Invent here: https://lnkd.in/eynJhaAm CC: Josh Diamant Lindsey Bedrosian James McGeehan Rinesh Patel Joe Wallace Angana Jacob Christopher J. Napoli, CFA Susan Doyle Chaim Haas Jennifer Molgano
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Michael Beal shared thisMichael Beal shared thisHow critical is high quality data as automation changes the financial landscape? 💻 Here's what you need to know about the power of data quality in fueling firms' decisions. 👉 Read more here: https://bloom.bg/3B3NESB #Data #Finance
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Michael Beal shared this#artificialintelligence is exciting 🚀 ; but successfully implementing it is HARD!!! 🤕 😠 I hope that you will join us tomorrow @12pm EST (click on free registration link below) as I lead a conversation with other Google Cloud clients & executives on the: - Mistakes made & lessons learned - Opportunities and areas of focus for continued improvementFrom Data to Decisions: Overcoming Challenges in AI-Driven Decision Making | Google C2C GlobalFrom Data to Decisions: Overcoming Challenges in AI-Driven Decision Making | Google C2C Global
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Michael Beal shared thisThe future of decision-making is here, and it's powered by #AI 🤖🦾💡 Join me at my first Google #keynotespeech, where we'll explore the possibilities and complexities of using AI for critical decisions. Virtual attendance is free at the link below! 👇 Let's pave the way for the future together! 🙏🏾 🚀 https://lnkd.in/g7uNiwhM 🚀
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Michael Beal shared thisFun times and thank you Quant Strats and WorldQuant for having me!Michael Beal shared thisDuring our morning Fireside Chat with David Rukshin, the CTO of WorldQuant, attendees had the opportunity to delve into a discussion about the future of quant investing, technology, and its impact. The conversation covered a range of topics, including how funds can support their quants amidst future uncertainty, as well as the technologies, processes, and priorities that quant professionals should focus on for the year 2023. Star speakers: ⭐ Michael Beal, CEO, Data Capital Management ⭐ David Rukshin, CTO, WorldQuant #QS23 #QuantStrats #NewYork #liveevent
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Michael Beal shared thisThis is an INCREDIBLE jump in #Ai 🤯🚀 #alpaca is a #meta #opensource #LLM trained by #GPT3.5 using #Selfinstruct method. It is high-performing, but not as good as #chatGPT. THAT’S NOT THE POINT. The amazing 99% cost difference is! 🤑💰 And fact it is A.I. creating A.I. ⛓💬 ChatGPT cost $4.6 million to train. Alpaca cost $600. It’s because it has A.I. creating prompts instead of humans training #LLMs This proof point will unleash a huge new wave of innovation — that i am excited to be a part of! 🔥🔥🔥🔥🦾🦾🦾🦾🦾💡💡💡💡 It also will be very interesting legal work on definition of reverse engineering code.. but well save that for another day… congrats Stanford University and put the demo site back up soon!!Meet Alpaca: The Open Source ChatGPT Made for Less Than $600Meet Alpaca: The Open Source ChatGPT Made for Less Than $600
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Michael Beal shared thisI have been thinking about this for the last 5 years. Simply want it to connect to LinkedIn and help me be more productive at conferences. I am sure it exists.. can someone send me a link?
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Michael Beal shared thisHindsight is 20/20. But this probably wasn’t a good idea…
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Michael Beal liked thisMichael Beal liked thisAs we celebrate the third night of Hannukah, my heart breaks for the families and friends mourning loved ones in Australia after the antisemitic violence at a Bondi Beach Hannukah celebration this weekend. What an unbelievably brave act of heroism by Syrian-born fruit shop owner Ahmed el Ahmed who disarmed one of the gunmen. https://lnkd.in/eaVTB3KsSyrian-Born Australian Who Tackled Bondi Gunman Hailed as HeroSyrian-Born Australian Who Tackled Bondi Gunman Hailed as Hero
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Michael Beal liked thisChristopher Golden is changing how we think about conservation as a public health solution—and he's mentoring the next generation of researchers as they work together to address the challenges facing human and planetary health. #HarvardChanlivingproofMichael Beal liked thisChristopher Golden is an associate professor in three departments, co-director of the concentration in climate change and planetary health, and director of Harvard T.H. Chan School of Public Health's program in nutrition and planetary health. Golden's work is changing how the world thinks about conservation as a public health solution. “For more than 25 years now, I’ve lived side-by-side with communities and really seen the ways in which climate change and environmental change have disrupted their society,” he says: https://lnkd.in/e-axrQGF. #HarvardChanlivingproof #livingproof #ourfacultyarelivingproof
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Michael Beal liked thisMichael Beal liked this🚀 Google just dropped the blueprint for the future of agentic AI: Context Engineering, Sessions & Memory. If prompt engineering was about crafting good questions, context engineering is about building an AI’s entire mental workspace. Here’s why this paper matters 👇 What’s Context Engineering? LLMs are stateless, they forget everything between calls. 🔹Context engineering turns them into stateful systems by dynamically assembling: • System instructions (the “personality” of the agent) • External knowledge (RAG results, tools, and outputs) • Session history (ongoing dialogue) • Long-term memory (summaries and facts from past sessions) • It’s not prompt design anymore, it’s prompt orchestration. Think of sessions as your workbench, messy but active. Sessions manage short-term context and working memory. Think of memory as your filing cabinet, organized, persistent, and searchable. Memories persist facts, preferences, and strategies across time and agents. Together, they make AI personal, consistent, and self-improving. My Takeaways: Context is the new compute, your system’s intelligence depends on what it sees, not just the model you use. Memory isn’t a vector DB, it’s an LLM-driven ETL pipeline that extracts, consolidates, and prunes knowledge. Multi-agent systems need shared memory layers, not shared prompts. Procedural memory (the how) is the next frontier, agents learning strategies, not just storing facts. Building an “agent” today isn’t about chaining APIs together. It’s about context architecture to make models actually think across time. The future of AI won’t belong to those who fine-tune models, it’ll belong to those who engineer context. “Stateful AI begins with context engineering.” This might just be the new foundation of agentic systems.
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Michael Beal reacted on thisNorway and Louisiana have a long history of being leaders in the maritime and vessel construction industry. With this partnership, we are reinforcing our status as global leaders and building partnerships for the future.Michael Beal reacted on thisToday, at the U.S. Embassy Oslo, the World Trade Center signed a Memorandum of Understanding (MOU) with Innovation Norway. This MOU will help foster collaboration between Louisiana and Norway in the maritime and vessel construction sectors through information sharing, trade missions, and promotion of trade and investment.
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Michael Beal reacted on this25 years and I'm still using the same headshot! My proudest moment in that time? A source told me he had come up with "The Max Bowie Rule" to never report all audit recoveries in one big chunk because he knew I'd spot them in their quarterly results! And if you want an entertaining read before the weekend, check out this recent column of mine: https://lnkd.in/eSf29_ek Here's to another 25 years!Michael Beal reacted on thisPlease join us in celebrating our editor-at-large Max Bowie's 25th anniversary working across the WatersTechnology brands. Hired in London as a Risk.net researcher in September 2000, Max is best known for his role as editor of Inside Market Data, where he built a reputation as a trusted journalist, renowned and respected throughout the data industry. We are lucky to have had him as part of the team for the last quarter-century. Cheers, Max!
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Michael Beal liked thisMichael Beal liked this🚨 New case alert! 🚨 I figured some love for women’s sports was long overdue. And what better team to focus on than the current WNBA champions, the New York Liberty? I’m grateful to Clara Wu Tsai and Joe Tsai for giving a behind-the-scenes look at how they’ve been turning around the franchise they bought in 2019, and to everyone else who granted interviews (including one of the GOATs 🐐 Breanna Stewart for proving her perspective as a player!). Can’t wait to see how this one plays out in the classroom!!! 🏀
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She Writes AI
🚺 Looking for fresh voices on AI and data, not the same old doomer and zoomer hype? Our latest She Writes AI digest includes: ✨ 4 Jointly Authored Collaborative Articles by: 1. Dallas Payne & Natalie Nicholson 2. Maribeth Martorana, CFA & Anna Levitt 3. Cristina Oliva Patrick & Nicole Stockenberger (Sovereign Insight Strategies) 4. Kristina Bogović & AI Meets Girlboss & Calder Quinn & Starlight 💟 10 Featured Articles by Hana Lee Goldin (2), Karo Zieminski (2), Hollis Robbins, Kim Doyal, Jennifer Hong, Daria Cupareanu, Maria-Cristina Muntean, and AI Meets Girlboss 🎲 10 Wildcard Picks by Jenny (Bingjie) Ouyang, Farida K., Alyssa Fu Ward, PhD, Elissa Malespina, Ida-Emilia Kaukonen, Claudia Ng, Marina T Alamanou, PhD, Giulia Spano, PhD, Shaili Guru, and Róisín B. plus 2 top-rated articles in 2 categories: 💯 Data & Analytics - Farida Khalaf 💯 Multiple AI Applications - Daria Cupareanu for a total of 📰 361 articles across 16 categories over 7 days, from 664 newsletters by SheWritesAI directory members. As always, here are two ways to use our digest to find articles and writers that interest you: 1️⃣ Browse the digest page at https://lnkd.in/dEU4w2S8 2️⃣ Use the searchable table of articles at shewritesai .org /articles You can also search our directory via shewritesai .org /search which has more information about the writers as well as a link to a recent article. Know a woman or nonbinary writer covering AI and data who might benefit from our free, supportive community? Share this link with them: shewritesai .org /join #SheLeadsAI #ArtificialIntelligence #EthicalAI #GenerativeAI #Community
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Tal Fishman
I’m sharing a short deck on a project I’ve been building: a Spec → Delete → Rebuild benchmark harness for evaluating LLMs in a way that mirrors real quant workflows. The idea is simple: * Pick a finished production quant model. Ask the LLM to first produce a no-code full specification of the main module, an observable contract. Delete the target module, then prompt the LLM to re-implement the module. * Validate with hidden behavioral unit/integration tests and tests reproducing known outputs. * Report a scorecard, not just pass/fail: tests passed, iterations-to-green, LOC, execution time, constraint violations, and robustness coverage. Why I built it: most benchmarks don’t truly replicate the experience of working with an LLM in a real production codebase. This harness is meant to measure *usefulness* in that workflow, not abstract “intelligence.” If you’re interested in AI evals or practical AI model comparisons, I’d love feedback. I'll be refining this idea as I work to implement it and apply it to testing out today's top two coding models: Claude Opus 4.5 and GPT 5.2 Codex. #LLM #AI #Quant #Benchmarking
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Michael Gunther, CFA
🚨 Big AI funding news via The Wall Street Journal: Anthropic is reportedly raising $10B at a ~$350B valuation, nearly doubling its valuation in just four months. This momentum lines up closely with what we highlighted in the Consumer Edge AI Spotlight: Q4 2025 Report. Our data shows engineering-focused AI is the fastest-growing category, and Anthropic was a standout, with ~450% spend growth as enterprises embed AI deeper into developer workflows. 📈 The signal is clear: AI that powers real engineering and production work is where durable value is being created. 🔗 Full report, containing insights on 130+ consumer facing AI companies, can be found here: https://lnkd.in/emSifVXN #AI #Anthropic #Claude #EngineeringAI #GenerativeAI Jesse Waldvogel
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Michael Hochstat
Yeah, that's a wild swing in the AQR Equity Market Neutral Fund (like QMNIX or QMNRX shares). The stat from Alexander Altmann at Barclays highlights extreme volatility in quantitative factor strategies right now. From recent performance data (as of early February 2026): - The fund showed a daily return of about **-1.06%** on what appears to be February 3 or 4, 2026 (aligning with "yesterday" in the original post timing around Feb 4). - Broader context: YTD returns were negative around -3.2% in some snapshots, but longer-term (1-year ~18-26%, 3-5 year ~21-22%) it has been strong overall. This fits the "crazy stuff in factor land" description—**market-neutral** strategies (long/short equity pairs aiming to cancel beta exposure) rely heavily on factor premia like value, momentum, quality, low vol, etc. When those factors rotate sharply or get crowded/unwound, daily moves can spike dramatically despite the "neutral" label. The back-to-back extremes (third-best day followed by third-worst since last July) suggest: - A sudden reversal in factor exposures (e.g., value crushing growth one day, then a snapback or other factor stress). - Possible quant crowding unwinds, similar to past "quant quakes" (like 2007 or 2018 events where similar strategies got hit hard). - Broader market rotation: Around the same time, there were notes on massive value vs. growth swings and equal-weight S&P outperforming cap-weighted. It's a reminder that while these funds target low correlation to markets and steady returns, short-term factor volatility can be brutal—especially in leveraged or crowded implementations. AQR's approach is systematic and research-driven (Cliff Asness roots), but no strategy is immune when the underlying signals flip fast. If you're tracking this for positioning or just watching the quant space, it's one of those periods where dispersion and factor timing matter more than broad direction. What's your take—seeing this as a one-off rotation or signs of bigger stress in systematic strategies?
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