DATA DAVE (@Dare2Digitize) header
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#Data for #Success If you don't dare, you won't digitize. Trust a Turtle

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Joined June 2010
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Is circular design the key to lowering carbon emissions? #EarthDay buff.ly/3k3fkLN rt @wef
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What works at one site doesn't always scale without a rethink. Before rolling an application out more widely, teams need to decide where processing should happen and how the system will recover when things go wrong. @TMobileBusiness Partner
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At #COP17Armenia, during the final plenary session, Parties to the Convention on Biological Diversity elected Ecuador to host the 18th meeting of the Conference of the Parties (COP18) in 2028. The announcement was broadcasted on UN Web TV: webtv.un.org/en/asset/k13/k1… #COP18Ecuador
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I'll be participating in a #ScienceUnderSiege panel at the @RawScienceTV Film Festival at Lincoln Center in NYC, Friday Nov 6 at 6pm. Come out and join us! rawsciencefilmfestival.com/2…
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Electrolyser competition drives new push to cut costs dlvr.​it/TW6zQM #HydrogenNow #H2View
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In a workplace shaped by constant change, professional growth depends on more than technical expertise. Human qualities guide collaboration, decision making, and trust, helping people contribute with clarity, responsibility, and balance at work. #SoftSkills #FutureOfWork
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An AI agent can initiate blockchain transactions and perform DAO operations, provided it has an authorized wallet and the required permissions. An agent can go beyond recommending an action and carry it out. People still decide the limits of that authority. Microblog @antgrasso Working with a blockchain is different from updating a conventional database. An application with database access can change records, but it cannot simply change a blockchain's shared state. Transactions must meet the rules checked by the network. The AI agent itself usually runs off-chain. It analyzes information and decides which action to request, while the blockchain validates submitted transactions and executes any relevant smart-contract code. The AI model does not perform its reasoning on the blockchain. A decentralized autonomous organization (DAO) allows a group to coordinate decisions and manage shared resources through blockchain-based governance. Despite its name, a DAO does not need AI to operate. But it can delegate specific rights or tasks to an AI agent. An agent could therefore cast a vote or initiate a treasury payment if the DAO's rules permit it. This does not mean giving the agent unlimited authority. The organization can define which actions are allowed and which still require approval from its members. Smart contracts can enforce programmed limits, although they cannot determine whether the agent's judgment is sound. The agent can act autonomously within its assigned role, without taking control of the organization's governance. #AIAgents #Blockchain #DAO
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ADIPEC 2026 is almost here, and the world's largest energy event is growing again. From 2–5 November at ADNEC Centre, Abu Dhabi: 2,260 exhibitors, more exhibition space and 1,800 speakers. More opportunities to connect. Join > adipec.com @ADIPECOfficial Partner. An expanded exhibition does more than welcome more visitors. It allows companies to show what they are building and gives potential customers more solutions to examine in person. For me, that is what makes a major industry event useful: a direct conversation can reveal whether a technology fits a real business need. Bigger in scale, bolder in ambition, greater in impact. A bigger, bolder, better ADIPEC experience. #ADIPEC2026 #ADIPEC #Energy
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A technology project can succeed technically and still deliver little value if the way people work does not change. I believe organizations should plan those changes as part of the investment, not after the technology has been deployed.
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As #COP17Armenia comes to a close in Yerevan, one message stands out. The challenge is no longer one of ambition. It is one of delivery. Whether we close that gap now comes down to choice and speed: the will to act, and how fast we do it. #Biodiversity #NatureForAll #COP17
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What happens when you take the operating discipline of fintech and apply it to one of the world’s most capital-intensive industries? Alan Chang joined Revolut at 21, became Head of Operations at 22 and Chief Revenue Officer at 27. After leaving at 28, he moved into energy and co-founded Fuse Energy with Charles Orr. Fuse is trying to combine software, renewable generation, infrastructure ownership and a technology-led operating model rather than behaving like a traditional electricity supplier. The company reported more than $300 million in annualised revenue by 2025 and has since been publicly described at a $5 billion valuation. But the more interesting story is bigger than one startup. We are seeing experienced technology operators move beyond software into energy, infrastructure, manufacturing and other physical industries. The next generation of tech companies may not simply digitise existing systems. They may own and rebuild parts of the physical infrastructure itself. The question is whether the speed and operating models of high-growth fintech can translate sustainably into sectors where capital, regulation, engineering and physical assets matter just as much as code. tradersdna.com/alan-chang-re… #Energy #Fintech #Revolut #FuseEnergy #RenewableEnergy #Technology #Startups #Infrastructure #DigitalTransformation
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Embodied AI is moving toward production, but capability is not proof of reliable deployment. Define the evidence needed at each stage. xpeng.com/au/news/01a0c826ab…
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What happens when AI becomes faster at scientific discovery than the institutions designed to verify it? We are entering a paradox. AI can map proteins, model new materials, analyse massive datasets and accelerate research from years to hours. DeepMind’s AlphaFold mapped more than 200 million protein structures, while AI systems are now being used across drug discovery, climate modelling, physics, agriculture and space research. But the same systems are also creating a growing integrity problem. Research audits have identified AI-assisted peer reviews, fabricated citations, synthetic scientific writing and cases where AI-generated “discoveries” still required human experts to determine whether they were scientifically meaningful. The question is not whether AI will transform science. It already is. The question is whether we can accelerate discovery without weakening the human judgement, imagination, verification and trust that science depends on. AI should expand the scientist’s capabilities, not replace scientific responsibility. In my latest analysis, I explore the opportunities, risks and SWOT of AI in scientific research — and the wider paradox of human-machine evolution. wisdomia.ai/ai-and-scientifi… #AI #ArtificialIntelligence #Science #Research #AISafety #AIResearch #Innovation #FutureOfScience #HumanMachine CC @YuHelenYu @efipm @enilev @JagersbergKnut @TysonLester @CurieuxExplorer @GlenGilmore @FrRonconii @chidambara09 @jeancayeux @mvollmer1 @Nicochan33 @RLDI_Lamy @pchamard @mikeflache @Fabriziobustama @Mack1510019 @ipfconline1 @PawlowskiMario @drsharwood @kalydeoo @baski_LA @AnthonyRochand @smaksked @Eli_Krumova @andresvilarino @gvalan @AI_4_Healthcare @bimedotcom @arlenenewbigg @NewsNeus @domingonarvaez1 @bamitav @jornalistavitor @jblefevre60 @FmFrancoise @MHcommunicate @Corix_JC @c4trends @smoothsale @amalmerzouk @PVynckier @bbailey39 @ralf_ladner @mary_gambara
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What happens when an AI system makes a decision that affects a customer, but nobody can clearly explain who approved it, who owns it, or who is accountable when it goes wrong? That is no longer a hypothetical governance problem. In financial services, AI is already influencing credit, insurance, investment suitability, fraud detection, customer support and compliance workflows. The challenge is that regulation still applies even when the decision is produced by a model rather than a person. Governance therefore cannot be reduced to policy documents. It needs clear ownership, risk classification, approval gates, explainability, monitoring and human accountability — especially for high-risk decisions. The principle is simple: machines can provide speed, scale and consistency. Humans still need to judge, explain and take responsibility. Read more: businessabc.net/ai-governanc… #AI #AIGovernance #AICompliance #FinancialServices #ResponsibleAI #RiskManagement #ArtificialIntelligence CC @YuHelenYu @efipm @enilev @JagersbergKnut @TysonLester @CurieuxExplorer @GlenGilmore @FrRonconii @chidambara09 @jeancayeux @mvollmer1 @Nicochan33 @RLDI_Lamy @pchamard @mikeflache @Fabriziobustama @Mack1510019 @ipfconline1 @PawlowskiMario @drsharwood @kalydeoo @baski_LA @AnthonyRochand @smaksked @Eli_Krumova @andresvilarino @gvalan @AI_4_Healthcare @bimedotcom @arlenenewbigg @NewsNeus @domingonarvaez1 @bamitav @jornalistavitor @jblefevre60 @FmFrancoise @MHcommunicate @Corix_JC @c4trends @smoothsale @amalmerzouk @PVynckier @bbailey39 @ralf_ladner @mary_gambara
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AI adoption has moved faster than AI control. That is the governance gap. In UK financial services, 75% of firms were already using AI, while 46% said they had only a partial understanding of the technologies they were using. Across large organisations, AI tools are multiplying faster than accountability structures around them. And the shift is accelerating. AI no longer only generates answers. Agentic systems can now book, buy, approve, send and act across workflows. Governance designed for software that recommends is not enough for software that acts. The question every board should now be asking is not simply: Do we use AI? It is: Do we know which AI systems we use, what they are allowed to do, who owns the risk, and can we prove it? AI governance has moved from principles and ethics statements into operational infrastructure: inventories, risk classification, controls, evidence, monitoring and named accountability. The period of voluntary, unhurried AI governance is ending. businessabc.net/the-urgency-… #AI #AIGovernance #AICompliance #AgenticAI #Risk #ResponsibleAI #ArtificialIntelligence #FutureOfBusiness CC @YuHelenYu @efipm @enilev @JagersbergKnut @TysonLester @CurieuxExplorer @GlenGilmore @FrRonconii @chidambara09 @jeancayeux @mvollmer1 @Nicochan33 @RLDI_Lamy @pchamard @mikeflache @Fabriziobustama @Mack1510019 @ipfconline1 @PawlowskiMario @drsharwood @kalydeoo @baski_LA @AnthonyRochand @smaksked @Eli_Krumova @andresvilarino @gvalan @AI_4_Healthcare @bimedotcom @arlenenewbigg @NewsNeus @domingonarvaez1 @bamitav @jornalistavitor @jblefevre60 @FmFrancoise @MHcommunicate @Corix_JC @c4trends @smoothsale @amalmerzouk @PVynckier @bbailey39 @ralf_ladner @mary_gambara
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US AI infrastructure spans energy stages: Big Tech has contracted >10 GW of nuclear capacity, Fervo Cape Station is operational, and SMRs are receiving construction permits. The key is not to confuse contracts, permits and power.
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The shift isn't from humans to AI—it's from managing tasks to overseeing teams of agents. As agents coordinate work and increasingly prompt us only when judgment is needed, our value moves toward designing guardrails, context, and decisions. #HyperagentPartner
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A familiar name in your inbox can feel reassuring. But is it really who you think it is? Attackers exploit trusted identities and everyday workflows. Making verification a habit is an important way to protect ourselves. @MSFTIssues link bit.ly/4i7ihdb v @antgrasso
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