Michael Whittle

Big news from the FINOS Governing Board 🌟 The Distinguished Engineer Special Interest Group is GO! ✨🧙🏻‍♂️ I’m absolutely thrilled to share that the Distinguished Engineer SIG proposed by Chris Booth (NatWest Group), Anthony Kesterton (Red Hat) and Mark Brotherwood (Davies) has been formally approved as a formal SIG under FINOS Labs. This is a huge milestone for financial services industry Distinguished Engineers. For the first time, DE’s from across financial firms have a recognised, neutral forum to: ☀️ Collaborate across organisational boundaries 🧚🏻 Share insights and best practices 🤖 Engage directly in open source projects and standards that drive industry-wide impact Until now, DE’s have lacked a structured space to contribute at this level. This SIG not only fills that gap, it creates an on-ramp for Distinguished Engineers to champion sustainable open source engineering within one of the world’s most regulated industries. This is the start of something special and I’m proud to see NatWest and Red Hat lead the way 🚀 Hats off to Chris and Anthony for pitching hard on behalf of the group 👏🏻 #FINOS #OpenSource #DistinguishedEngineer #FinancialServices #Collaboration #RedHat #NatWest #OpenStandards #EngineeringExcellence #DEsig

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It’s eye-opening how beneficial tokenization can be for enterprises. Because data tokens are non-sensitive, they enable analysis and sharing without exposing raw values, minimizing the risks of a data leak. Learn more. https://bit.ly/48Jv2X1

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Trader breaks down CCJ stock ownership and performance, highlighting Seagate and Western Digital's strong results. Market insights in a nutshell. Not financial advice. Results may be simulated. #StockAnalysis #Trading #CCJStock #Seagate #WesternDigital

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Rob talks about recent AI improvements, including a crucial fix for a trading bot bug that caused missing exit conditions. Ensuring greater reliability and accuracy in automated trading strategies. Not financial advice. Results may be simulated. #AIBot #TradingAI #AlgorithmFix #TechUpdate

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AI has made execution faster. It has not made commitment cheaper. This is the distinction most technology leaders are not making clearly enough right now. And the cost of missing it compounds quietly, until someone inherits the answer. In my first post of Season 2 of Systems and Sutras, I write about something I encountered early in my career. A decision made under delivery pressure that was already live by the time I arrived. Synchronous where it should have been asynchronous. Fast where it should have been deliberate. By the time anyone questioned it, the system had reorganised itself around that decision. Partners had integrated against it. Contracts referenced it. Changing it would have required a migration window nobody had appetite to fund. A temporary decision had become permanent architecture. AI accelerates this pattern in two distinct ways that are worth separating carefully. The first. speed surfaces existing weaknesses faster. Ownership gaps, architectural fragility, unclear boundaries. These were always present. AI simply removes the buffer that used to obscure them. The second is specific to AI-assisted development itself. Code that is locally coherent and systemically fragile, written faster than the organisational immune system can respond. Both risks matter. But they require different responses. And conflating them leads to the wrong one. The full post covers both. It also covers why reversibility is a governance discipline, not a technical preference. And why the leaders who will define this era are not the ones who move fastest. They are the ones who know which decisions to slow down, and why. Season 2 is about responsibility when execution is cheap. This is Post 1 : https://lnkd.in/eMVXKNac Execution ends. Commitment begins. Few notice the crossing.

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I’m proud that Broadridge is leading the settlement of tokenized real assets, with our Distributed Ledger Repo (DLR) platform settling $5.9 trillion in processed repo trade volumes in August. Amidst this growth, aggregated market data from DLR is now available on RWA.xyz through Kaiko’s new application on the Canton Network. If you’d like to learn about our commitment to unlocking new tokenization opportunities across global capital markets, let’s connect. http://spklr.io/6041ByzVP

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84.6% — Gemini 3 Deep Think Sets a New Benchmark in AI Reasoning 🚀 Google recently announced that Gemini 3 Deep Think achieved an 84.6 % score on the ARC‑AGI‑2 benchmark, a result verified by the ARC Prize Foundation. This is one of the highest reported scores on this challenging abstract reasoning test. What ARC‑AGI‑2 Measures ARC‑AGI‑2 evaluates AI’s ability to generalize and solve novel abstract reasoning puzzles — tasks designed to go beyond memorization or pattern recall. What the Official Blog Actually Says ✅ Deep Think is an advanced reasoning mode of the Gemini 3 family. ✅It set a verified 84.6 % on ARC‑AGI‑2. ✅This milestone demonstrates enhanced abstract reasoning capability within a specialized inference mode. Why It Matters AI reaching this level on structured reasoning tasks is a milestone for applied intelligence — offering new opportunities in strategic decision-making, problem-solving, and innovation. 💡 Discussion Point: What does it mean for strategy and governance when AI achieves near-human performance on structured abstract reasoning tasks? #ArtificialIntelligence #AIResearch #AIReasoning #AIBenchmarks #GenerativeAI #AIStrategy #TechnologyLeadership https://lnkd.in/gYJaVpjh

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Tokens are consequences. Infrastructure is the decision. The next real evolution in crypto will not come from new assets, but from systems that integrate with existing financial architecture. Interoperability, compliance alignment and institutional trust will define who remains.

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The SEC's latest move to enable generic listing standards for spot crypto ETFs means Solana‑based ETFs may hit the market much faster. At NODE40 we're leaning into this by reinforcing our internal auditing of staking rewards, enhancing our data pipelines for derivative metrics, and ensuring proofs of custody and reserves are clean and auditable. If you build with transparency, now is the time to double‑down. #Solana #CryptoETFs #Derivatives #DataIntegrity #NODE40 https://lnkd.in/eMHaeV8p

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Token-Oriented Object Notation(TOON) It is a new, lightweight data serialization format designed specifically to optimize data exchange with Large Language Models (LLMs). It is often referred to as "JSON for LLMs" because its core purpose is to represent the same structured data as JSON while achieving massive savings on token on usage. Few key points about toon: * Token Optimization: TOON is a data serialization format designed to significantly reduce the token count of structured data passed to and generated by Large Language Models (LLMs * Token Savings: It typically achieves 30-60% fewer tokens compared to formatted JSON, directly lowering inference costs and improving speed. * Minimalist Syntax: It minimizes the use of repetitive punctuation (quotes, braces, commas) that consume tokens in formats like JSON. * Tabular Arrays: Its key innovation is handling uniform arrays of objects by declaring keys once (like a CSV header) and listing data in comma-separated rows, eliminating the need to repeat key names for every object. * Indentation-Based Nesting: It uses indentation (similar to YAML) to represent nested object structures. * Primary Use Case: Optimal for tasks where token efficiency is critical, such as in Retrieval-Augmented Generation (RAG) context injection and instructing LLMs to output clean, structured data. https://lnkd.in/gNRMgkp6

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Private markets are evolving — and access is expanding. Excited to see Templum enabling new investment opportunities through a collaboration with SoFi, giving eligible investors exposure to innovative companies like OpenAI, Perplexity AI, and Colossal Biosciences. #PrivateMarkets #FinTech #Innovation

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#ICYMI Why AI models trained on tokenized data are nearly 2x as accurate as those trained on masked data. Get the full research breakdown in the on-demand webinar. https://bit.ly/453dUso

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We’re excited to announce that Copper.co has partnered with Chorus One to bring institutional-grade TON staking to Copper clients via the Chorus One TON Pool! ✅ Seamless custody-to-staking integration on Copper’s award-winning platform ✅ Enterprise-grade security with MPC-based custody and ISO 27001 certified infrastructure ✅ Stake TON with low minimums and unlimited delegators, purpose-built for institutional scale ✅ Full regulatory confidence for global clients ✅ Transparent, predictable rewards and streamlined operations This collaboration unlocks scalable, secure TON staking for institutions, empowering you to participate in the rapidly growing TON ecosystem with confidence and operational ease. Ready to elevate your TON strategy?
Learn more: https://lnkd.in/ejAYWHJJ

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What Institutional Means "Institutional” doesn’t mean large. It means: • Predictable processes • Documented decisions • Enforceable controls • Clear escalation paths Scale comes later. #Institutional #Governance #Execution

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TOON can significantly boost AI pipeline performance by shrinking prompt sizes, cutting compute load, and accelerating interactions across models and services. With a projected 30–70 percent reduction in tokens, it has the potential to meaningfully lower the cost of using LLMs. However, for deeply nested or non-uniform data, JSON may be more efficient. https://lnkd.in/gV8qiWSF

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I’ve seen firsthand how much time even the best teams spend on personalised client communication. Explaining portfolio and strategy performance, connecting outcomes to market events, repeating the same analysis client by client. This is the real inefficiency in finance: personalisation doesn't scale. Private bankers know a one-size-fits-all 60/40 portfolio fits no one, but current tools make customisation painfully slow. Clients get less personalisation than they deserve, and senior talent spends time on tasks that should be done with the click of a button. AI can help solve this, but not by wrapping ChatGPT around portfolio holdings. LLMs can explain beautifully, but they can't run the numbers and weren’t built for regulatory requirements. The bottleneck in finance isn't model intelligence; it's the infrastructure underneath. So we built the infrastructure first: a quantitative engine designed for AI to orchestrate. The AI explains and coordinates and the engine computes and traces every step. Getting these to work together reliably is its own frontier. Traceability, guardrails, coherent multi-agent behaviour, cost management at scale, all in a field where you're inventing the architecture as you go. This is what we've been building at Analyzera. Not an AI wrapper, but the actual machinery. Draft personalized client reports on portfolio performance against a Fed decision in seconds, not hours. Get instant insights into concentration risks or diversification gaps and run simulations to take action. Construct custom allocation strategies with the speed of a conversation, not a week-long analysis. Built by a team from J.P. Morgan. More details below...

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🚀 Big news from FINOS! We’re excited to welcome Bhupesh Vora (RBC Capital Markets) as Chair and Sitija Sarkar (BlackRock) as Vice Chair of the FINOS Governing Board. Together with our Governing Board and community, we’re entering a new chapter: ✅ Embedding open source into the core fabric of global finance ✅ Driving ROI through open standards like FDC3 and the Common Domain Model (CDM) ✅ Advancing collaboration on AI Governance, cloud compliance, and industry interoperability As Bhupesh Vora put it: “By 2030, FINOS technologies and standards will be essential components of the industry’s core platforms, workflows, and regulatory frameworks.” 🌍 The era of open source as a business imperative in finance is here. 🔗 https://hubs.ly/Q03FMyWb0 #opensource #AIinFinance #fintech #financialservices #CDM #FINOS #OSFF2025 #regtech

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