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Articles by Fernando
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Reflections on a landmark event: Creating real, actionable impact from AI for the UK
Reflections on a landmark event: Creating real, actionable impact from AI for the UK
Fernando Lucini, Global Data Science & Machine Learning engineering Lead, Accenture A couple of months ago, I was a…
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Think big. And scale with intention.Jan 6, 2020
Think big. And scale with intention.
Break through the barriers to scaling AI and follow our roadmap to maximise the ROI of your AI projects. I bet you…
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Buy vs BuildOct 17, 2018
Buy vs Build
Situation Buy vs Build vs Partner. It’s not a new question.
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AI and ScalingDec 19, 2017
AI and Scaling
I was fortunate the last 2 or so weeks. I got to work with a small team of very talented people.
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AI and the person behind the curtainAug 31, 2017
AI and the person behind the curtain
I'm sure most of you have seen the Wizard of Oz. Dorothy and her pals go to the emerald city to see the Wizard of OZ.
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AI and TrustJul 25, 2017
AI and Trust
I’ve been thinking a lot about how big companies adopt AI. How you scale production.
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AI and Trapped ValueJun 28, 2017
AI and Trapped Value
This week I obsessed about technology orthodoxy. The generally accepted belief or dogma of how things should “work” or…
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AI....Doors and DoorknobsJun 20, 2017
AI....Doors and Doorknobs
One of my favorite people in the world, Mr Brian Weiss (https://www.linkedin.
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AI. To amplify, to augment or maybe to blend?Jun 12, 2017
AI. To amplify, to augment or maybe to blend?
A few years ago, a very talented group of people helped me in the launch of a product. This product sat squarely in the…
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AI is the new UI....what does it all mean...to me?May 31, 2017
AI is the new UI....what does it all mean...to me?
How many times today will you open a website or an app on your phone/computer/tablet for the first time? I will be…
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Activity
7K followers
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Fernando Lucini shared thisAs my people are tired of hearing me say, it’s never been easier to build a demo- but making AI work inside a company is a very different and awesome challenge. Embedding it into the real world of workflows, earning trust, and governing it takes discipline, not hype. Its also immensely rewarding. I enjoyed having a thoughtful conversation with Dr Katy Ring from [@Diginomica] about why this work matters. Read more here: https://lnkd.in/e-D9ruvC Matt Prebble John Gibson Marc Warner Assia Iossifova Natalie de Freitas Christopher LaneHow Accenture is minding the AI enterprise adoption gapHow Accenture is minding the AI enterprise adoption gap
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Fernando Lucini shared thisOne of my favourite events are the business breakfasts we do in Dublin. i get to go to Dublin, speak as fast as a want and be understood and be grumpy without being judged :) Joking aside thanks Hilary O'Meara and team for having me. Its clear to me thats whilst AI is the only new game in town and it will no doubt change how we work and how we operate companies, there is still a lot of work needed to scale....this is the beginning of this journey....and as Frank Herbert said.."Beginnings are such delicate times" So lets openly talk about how its hard work to build value but also celebrate that this muscle we are building is critical to the future. amazing to join Ian Howie Rachel Eardley Colin Banville Jessica O'Brien Denis Hannigan on stage to share thoughts on how to succeed in Ai at the moment. Accenture UK & Ireland Accenture Matt Prebble
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Fernando Lucini shared thisI had the opportunity this week to present at the Allianz Data & Ai Summit Allianz. I know I'm biased as I love working with my Allianz friends, but that not withstanding, I was incredibly impressed with the commitment to customer value and the passion to use AI to solve interesting and important challenges..whilst being very grounded to the realities of the technology today. A great balance of dare to change, focus on what works and scale the value at speed. I also made a new cool friend in Sascha Poggemann, I look forward to geeking out more with you in the future. Thank you to Nino Nicotra, Dr. Inka Weinzierl and the Allianz family for hosting me! Accenture DACH Accenture Marco Huwiler Christina Raab Florian Schaudel Christian Uhl Barbara Karuth-Zelle
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Fernando Lucini shared thisIt was a real pleasure to do the key note and two incredible panels for the Macquarie Technology in Focus Macquarie brought together leaders across telecoms, data, and emerging technology for its inaugural event Technology in Focus: From Legacy to Leading Edge. A great set of speakers and audience to discuss how the infrastructure behind AI and data continues to evolve. I was truly fascinated to hear all about how Macquarie are working on recovering copper networks so the materials can be recycled and capital injected into new technologies such as AI Factories. Then two incredible panels with Anthony Hills, Tim Haines, Colin Bannon, Tom McDonell, Michel B., Jeremie Eliahou Ontiveros, Giovanni Della Pesca it as a blast, from the pressures on supply and demand for AI, the realities of building an AI Factory, networks going from "sucking to blowing", how networks will manage the edge, etc...Europe really has to push the "go" button. It was really amazing to spend time on this part of the AI problem. thanks a lot Macquarie Group Lou Tricarico Emma Satori Tom McDonell for everyhing. Accenture Accenture UK & Ireland Matt Prebble
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Fernando Lucini shared thisI want to do a shameless plug for my friends Ray Eitel-Porter, Dr Paul Dongha and Miriam Vogel's new book. A real study of how to use AI safely in the real world. From people that truly care about the direction this is all going in. Ray Eitel-Porter it did make me smile to see my tiny anecdote in there. :) https://lnkd.in/e7eyrq4T
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Fernando Lucini shared thisJust back from an incredible panel at @Royal Television Society’s #RTSConvention on AI: Embracing The Opportunities! 🤖💡 Huge thanks to my fellow panellists Matt Clifford and Kian Katanforoosh for a lively discussion on the complexities and challenges of #AI adoption. There was always the possibility that we all agree but we managed to disagree some :). And special thanks to our chair and moderator Zoe Kleinman for keeping us on our toes and being an awesome host! 👏 Key takeaways: ✨ Practical application (do more, talk less...said the three people talking on stage), building trust, educating ourself and strategic investment are key to unlocking #AI's full potential. ✨ There is massive hype, but volumes of truly amazing inventions and advancements in the land of AI also... building robustness and reliability in AI is very important if we want calculable impact in the coming years. 📸: Richard Kendal/RTS Accenture UK & Ireland Matt Prebble Shaheen Sayed Gavin Mann
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Fernando Lucini shared thisAlways fun to share an opinion… but I might be slipping into grumpy engineer territory here. My frustration isn’t with dreaming big about AI—it’s with the narrative that glosses over the real challenges. While a whole world of engineers and scientists tackle complex issues to make AI truly usable, it often gets portrayed as if those hurdles are already behind us. That storytelling undermines genuine progress and trivialises the work being done. So here are some thoughts about benchmarking and Small Language Models (SLMs) in enterprise contexts—from our collaboration with ComputerWeekly.com and the ever-insightful Adrian Bridgwater. I hope this sparks a more grounded conversation about what it really takes to build responsible, reliable AI. Matt Prebble Christopher Lane Gavin Stephenson Pankaj Sodhi https://lnkd.in/eFJ5htWr
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Fernando Lucini shared thisEver the innovative Bank, this collaboration with Amazon Web Services (AWS) and Accenture will accelerate the mission of Natwest. Much innovation is needed in data foundations more broadly and its awesome to see this commitment to change in this area. Amazing collaboration from the team Nina Raphael Gavin Stephenson Amit Bansal and NatWest Group Zachery Anderson Congratulations to all involved!!!!!Fernando Lucini shared thisIn today’s banking industry, banks need to be able to develop and drive customer advocacy by personalising customer experiences and building deeper connections. I am pleased to share that Accenture and Amazon Web Services (AWS) announced a new collaboration with NatWest Group to transform and modernise the bank’s digital, data and analytics capabilities. This new 5-year collaboration will enable NatWest to provide more intuitive, engaging and personalised services to its 20 million customers – by anticipating, understanding and responding to clients’ needs faster and more effectively. It will also provide the bank with access to new AI capabilities and help to foster a data-driven culture. So excited to be part of that journey! Find out more: https://lnkd.in/eerzqyzD] Accenture UK & Ireland Matt Garman, Rob Jackson, Scott Marcar, Zachery Anderson, Victoria Cleverley, Karen Dewar, Paul Thwaite Julie Sweet, Shaheen Sayed, David Parker
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Fernando Lucini shared thisBack to Cambridge after a wonderful day at TECH by Handelsblatt. Had lots of conversations about AI for sure, but even more about how Europe can and should push harder on the world stage of technology — and the need for sovereign AI. It was eye-opening to talk to some of the most incredible European companies — ones that design, build, and distribute important, differentiated, and in some cases irreplaceable products and services, famous the world over... but who still talk with unnecessary humility. Let’s be bold. Let’s ride the wave of AI innovation and build a competitive landscape in our own backyard. Thanks so much to Marc-Steffen Unger (www.ms-unger.de) for the great pictures. Christina Raab Tobias Regenfuss Kathrin Schwan Matt Prebble Luise Klussmann Daniela Bender Accenture Accenture DACH #TECH2025 #AI #DigitalSovereignty #IndustrialAI #OpenSourceAI
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Fernando Lucini liked thisFernando Lucini liked thisOne of One Automotive: Advanced financial instruments blending automotive expertise, investment excellence and data & AI to disrupt classic car investments In today’s volatile world, a growing number of investment strategies are increasing the weight of alternative assets to de-risk portfolios. Within alternatives, classic and collectible cars are a “blue ocean”: market assymetries, strong and continued historical appreciation, low volatility – even in times of massive disruption -, liquidity and mobility, in an asset class where demand continues to grow, and supply remains stable, or even decreasing. However, it is also a complex asset class – One where transactions have been driven by intuition & passion for decades. We have founded One of One to change that. After a 20-year career at BCG helping clients gain competitive advantage through tech, data & AI, I am launching this new venture with the best wingman I could have dreamed of, Javier Aguilar. Javier brings more than 15 years of personal and professional investment in this sector, as well as broad & deep connections across the automotive and business landscapes. Today, a new chapter begins. What is One of One? A 25 M€ fund regulated by the CNMV (the Spanish National Securities Market Commission), focused on applying Artificial Intelligence and advanced data analytics to a market traditionally driven by intuition and passion, introducing an unprecedented layer of precision to the sector. We have already secured 50% of committed capital, with ongoing operations yielding excellent returns. My sincere thanks to the investors and Family Offices who have placed their trust on us from day one. #BusinessStrategy #PrivateEquity #WealthManagement #Innovation #AI #ClassicCars #AlternativeAssets #Investment #Porsche #Ferrari #Entrepreneurship #DataAI #Investments
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Fernando Lucini liked thisFernando Lucini liked thisGrateful for the San Francisco Business Times’s recognition. I’m proud to live and build in San Francisco. And as Mayor Daniel Lurie 丹尼爾·羅偉 says, “let’s go San Francisco!!!”
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Fernando Lucini liked thisFernando Lucini liked thisI'm delighted to be taking on a new role leading Customer Service globally for Accenture from 1st April. As Global Lead, Service, Accenture Song, the team I lead will take on responsibility for all sales and delivery of all our customer service work within Accenture. I'm excited about how we can better serve our clients as one Reinvention Services team as we bring together all our people who provide advice to clients on their service design, experience, strategy and operating model, as well as those that build the technology platforms that their service workforce depend on and (increasingly) the Conversational and Agentic AI platforms that customers and service personnel want to use; AND our amazing people all over the world provide expert service, in all channels, when only a person will do. This unique mix of capabilities, across all geographies and industries, and our commitment to providing the best service experience for our clients, is what makes this team special and I'm proud to lead it. Thank you Ndidiamaka Oteh Julie Sweet Manish Sharma for the opportunity.
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Fernando Lucini liked thisToday marks the beginning of an exciting new chapter; I am joining Insight as CEO, effective April 13. Stepping into this role and joining the Insight team is a privilege. Insight has always stood for something unique in the market — a rare combination of technical depth and scale, a unique ability to help clients seamlessly integrate hardware, software and services, and a genuine commitment to our people, our clients, and our partners. We are at a pivotal moment. #AI requires organizations to move beyond experimentation towards measurable impact, and we have work to do to meet the pace of this transformation. Our focus is clear: to accelerate our position as the world’s leading Solutions Integrator to help our clients realize the full potential of AI. I’m energized by the work ahead and confident in what we will build together.Fernando Lucini liked thisA bold new chapter for Insight begins today. We are thrilled to announce that Jack Azagury has been appointed as Insight’s next Chief Executive Officer. Jack is a longtime technology executive, having spent nearly three decades at Accenture, most recently as group chief executive for its Consulting business, where he helped clients navigate digital and AI-based transformations. Jack understands that in the AI era, our mission of solving our clients’ technology challenges by combining the right hardware, software, and services will be vital in bridging the gap between emerging technology and measurable business impact. And his appointment will accelerate our ability to deliver even greater value for our clients and partners. What will not change: our people, our values, and our commitment to client success. We are simply moving faster to meet you where the market is headed. Please join us in welcoming Jack to the team! Read the full announcement here: http://ms.spr.ly/6001QsZ85
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Fernando Lucini liked thisFernando Lucini liked thisAs AI advances rapidly, the next few years will be hugely consequential for the world. For any company that isn't AI-native, thriving will mean a difficult process of adaptation. To succeed, they need partners with an unusual set of capabilities: deep technical expertise, plus the ability to deliver transformation at scale. Today Faculty has officially joined Accenture. Together, we have created one of the few organisations in the world equipped to lead this historical transition. We made this decision for the same reason we started Faculty in 2014 - because we believe the AI revolution will only go well if the technology is deployed both widely and safely. I’m excited to work with everyone at Faculty and Accenture in the next phase of our journey together.
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Fernando Lucini liked thisFernando Lucini liked thisDelighted to share that I’ve been nominated for the Accenture UK & Ireland Outstanding Women in AI & Data Awards 2026. Thanks to the team I work with who are always striving for excellence and my mentors putting in the time to pass on their experience and advice. #WIAIDAward #GivetoGain
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Fernando Lucini liked thisFernando Lucini liked thisAn agent is only as good as the context it's built on. Huge congratulations to the Workera and Udemy AI teams for building what is likely the largest RAG ingestion pipeline in learning and HR tech. Workera's agent (Elo) is now more deeply integrated than ever with Udemy Business – pulling from a fresh catalog of 31,000+ courses and 2.4M modular learning items, with rich metadata and semantic embeddings built for fast and precise retrieval. Joint customers get access to the most current Udemy content available. And critically, the infrastructure is now in place to keep it that way automatically.
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Fernando Lucini liked thisFernando Lucini liked thisGreat to go on The Rest is Money podcast with Robert Peston and Steph McGovern to discuss: - How Faculty's acquisition by Accenture will accelerate the safe widespread adoption of AI - The need for nuance around job displacement - and to view it as reflection of long term technological progress, not a single moment in time - Why banning access to AI in schools is wrong - The industrialisation of software development and the parallels with cotton production - Valuing artisan, artistic jobs rather than purely economic ones - and how AI will make us more human - Tax breaks as a necessary trade off to attract founders and persuade them to scale in the UK Link to episode in the comments. Love to hear your thoughts
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Patents
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Processing an Action Based on an Attribute
Issued US 20160232034
In one implementation, an action may be processed based on an attribute. An attribute of an action may be determined. A complexity value of the action may be evaluated based on the attribute and independent of a system state. The action may be positioned in a workflow based on a time unit length for execution of the action.
Other inventorsSee patent -
Data point on a display
US US 20160163074 A1
As the amount and complexity of data obtained and processed by computers today are rapidly growing, it is important to find new ways of presenting the data to the users in a coherent and insightful manner, allowing the users to obtain maximum data insight in minimum time.
Other inventorsSee patent
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Nitin Joglekar
Research Interests: <br>(i)… • 3K followers
Sankar makes an excellent point about agents allowing foundational redesign of processes. How will this alter operations processes and supply chain configurations? #agentic #designthinking #Supplychain #Configuration Production and Operations Management Society (POMS)?
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Gaurav D.
Strategia • 2K followers
There's a lot of chat around 'Context Engineering' as an hyper important element in AI solutions right now. From my experience architecting and building enterprise solutions, context engineering has truly become one of the most important elements along with building strong eval pipelines and innovation around the UI. It's also one of the most challenging things to get right because this is where we are getting into the heads of domain experts to truly understand how everything works, what they are trying to achieve and then utilise our own expertise in analysing 'are we replicating inefficient processes?' , 'can we use a different way (much better way) to achieve even stronger results?' etc. As the underlying models get stronger and stronger, engineering the right context at the right time is going to become even more important in scaling agentic solutions.
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Chris Williamson
3K followers
GenAI has changed how organizations think about quality. How do you evaluate if a response is “good”? Debug multi-step prompt chains? MLflow 3.0 includes new capabilities that solve common challenges around quality measurement, observability and continuous improvement. A unified platform to trace, evaluate, debug, and improve GenAI applications — with full support for traditional ML and deep learning. Get started with MLflow 3.0 in open source or on Databricks.
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Lee Thorpe
Dataiku • 1K followers
I've now seen feedback from many CDOs at Big Data London that the event felt too heavily skewed towards agentic AI, while many CDOs are still focused on deriving tangible value from core data assets. There is a disconnect: technology vendors, especially as event sponsors are pushing highly complex, agentic AI solutions that much of the industry is not yet ready or resourced to implement. What businesses need now are practical, scalable data solutions that drive measurable impact. There's a risk that overemphasis on advanced AI could alienate stakeholders still on their data maturity journey. Do we need to go back to basics first?
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Chris Williamson
3K followers
In a new opinion piece for @NODE, @Databricks’ @Maria Zervou argues that in 2026, AI will stop being a side experiment and will instead become something organisations genuinely rely on day to day. She highlights that the real differentiator won’t be flashy models, but solid data foundations, clear governance and people who are confident working alongside AI. Read her thoughts here 👉
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John Hauxwell
AIdentity UK • 2K followers
Turn fragmented data into a trusted business asset with a clear governance blueprint. Define roles, enforce policies, and track quality metrics so your teams spend time on insight — not rework. Aidentity.uk brings architecture expertise and practical data solutions to speed analytics and AI adoption. Learn how to operationalise governance for reliable, reusable data: https://wix.to/ck1zLkY 🔍📊 #DataGovernance #DataStrategy #AIReady
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Tiankai Feng
Thoughtworks • 39K followers
Ever since Sadie St Lawrence and I connected years ago for some collaboration with Women In Data™️, I've always admired her passion and expertise for data science and AI, and it's been really inspiring to follow her journey. This is why I was so excited to see her publish the book "Becoming an AI Orchestrator" and as expected it was a great and insightful read for many reasons. As a fellow musician, I really enjoyed the music analogies of how knowledge workers need to shift from being a musician to be an orchestrator, and why being an "orchestrator" is more critical than being a "conductor" in todays times. Other highlights for me were: 👉 The overview of Gen AI application categories across creative tasks, analytical tasks and hybrid tasks 👉 The implications of different types of intelligence for our relationship and interactions with AI 👉 The concrete examples of applying AI in different business functions 👉 An iterative process for AI adoption that starts with identifying human tasks 👉 How to get started in defining the right AI guidelines and policies, including an important part about how to address Bias 👉 A playbook on how to thrive in the age of AI by following certain golden principles Across the entire book Sadie mentions lots of her experiences and stories of how she uses AI in her day to day, which together with other parts shows us a truth that I couldn't resonate more with: doing the right and valuable things with AI starts with every single individual. And reading this book will definitely help you do that. I highly recommend this book to anyone who wants to know how to use AI to enrich their life, their career and our collective future - which ideally should be everyone. #aistrategy #book #tiankaistuff
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Michael Lombardo, MS, PMP (Ret)
Scalytics • 585 followers
Data that isn't accessible always leads to inconsistent results which in turn lead to inaccurate decision-making. Those inaccurate decisions lead to potential financial and operational losses or more drastic outcomes. Federated data processing makes siloed data usable, learn how below..
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Nevada Pascolini
Elio. • 5K followers
Two weeks ago I attended Big Data London Here's a breakdown of how it went down for those who are interested in attending next year, curious about what kind of learnings there were, and want to know the industry trends that are shaping data right now: Key takeaways: → Data governance needs reframing: it's an enabler, not a blocker → AI governance is still the Wild West - every company is figuring it out → Context is emerging as a critical layer in the data stack due to AI → The way we understand BI is changing rapidly → Quality not quantity for AI agents → Too many data teams are misunderstanding data products Also: personal thoughts on the event Full write-up on my Substack: https://lnkd.in/dve9Uxbz
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Andy Graham
Rentokil Initial • 2K followers
The UK is sitting on one of the most valuable datasets in the world and most of it is still locked away in government systems. But the National Data Library project could change all of that. Whether it becomes another well meaning initiative or a genuine economic catalyst depends on what happens next. Here’s my take on why this moment matters. #Data #NDL #UKGovernment #Datasets #PublicData #Economy #UK
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Nikolay Baakh
NDA • 929 followers
We live in an era of unprecedented access to information. We’ve moved from biological memory to writing, to digital storage, and now, to Generative AI. For senior professionals with deep domain expertise, AI is an incredible force multiplier. It acts as a high-level executive assistant, accelerating workflows and retrieving data instantly. However, I am seeing a concerning trend among emerging talent that acts as a career "silent killer." The Outsourcing of Critical Thinking. It is tempting to view tools like ChatGPT as a "solve button" for complex deliverables. You input the prompt, get the code or strategy, and submit. On the surface, productivity skyrockets. But underneath? A dangerous hollowness is forming. If you bypass the "struggle" - the friction of debugging, the research of foundational principles, and the manual trial and error - you are bypassing the very mechanism that builds seniority. Employers eventually notice the difference between a specialist who understands the architecture and one who merely prompts it. The former is an asset; the latter is replaceable by the next update of the model. In part 2, I’ll dive into the three specific areas where this over-reliance creates a ceiling for your career growth. #AI #CareerGrowth #TechTalent #FutureOfWork #SkillDevelopment
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Bill Roberts
TPXimpact | B Corp™ • 518 followers
I really like this from the ODI: interesting experiments on the new kinds of interface needed to support easy access to datasets by AI agents, and also a reminder that much of "AI-readiness" is doing the basics of data publishing well - consistent structure, clean data, good titles and metadata
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Jack Snape
Department for Science… • 2K followers
Yesterday we published the 2024 AI Sector Study, our annual analysis of the UK’s AI sector, providing estimates of the scale, scope and growth of firms developing AI products and services in the UK. Some key insights: - Companies: From 2023 to 2024, the number of AI firms jumped by 58% to around 5,800. - Employment: UK AI sector employment grew by 33% to around 86,000. - Revenue: Revenue saw a massive increase of 68%, reaching around £23.9 billion. - Gross Value Added (GVA): The sector's GVA more than doubled, increasing by 103% to £11.8 billion. - Investment: Investment in dedicated AI companies rebounded to £2.9 billion, surpassing the previous 2022 record. - Lots more in the report including breakdowns by sub sector, business size, region, and evidence on barriers to growth. Great to partner with Perspective Economics, Ipsos, and Glass.AI on this. And brilliant work from the DSIT team - Maeve Fitzmaurice, Luke Yates, and Mark Wingham https://lnkd.in/eM4_Jiev
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Demetrius Griffin
Gryphon Data Processing • 250 followers
Guardrails and Graphs: Designing Trustworthy Enterprise AI The new era of enterprise AI isn’t just about deploying bigger models - it’s about building governable ones. In the next edition of The Data Pipeline Pulse, I explore how guardrails, GraphRAG architectures, and agentic workflows are shaping the blueprint for trustworthy AI systems. From responsible deployment to integrated governance, this is where architecture meets alignment. #DataPipePulse #EnterpriseAI #LLM #RAG #GraphRAG #ResponsibleAI #DataEngineering #AgenticAI
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Nishant Sharma
1K followers
Animesh Kumar and Travis Thompson 's latest piece on MCPs, Data Products, and unified data platforms is one of the clearest architectural framings I've seen. Worth reading. The thesis: three standards are converging to solve one structural problem. Data Products unify around economic outcomes. DDP industrialises their creation. MCP standardises how AI agents interact with them. The reference architecture stacks these into layers — from cloud infrastructure at the bottom, through core platform services, up to user-facing apps like Analytics Tools, SQL Interface, and Knowledge Graph at the top. It is a compelling framing. And it got me thinking about a question I can't let go of. I think if MCP becomes the standard interface through which AI agents interact with data, the first thing an agent needs is meaning. Not tables. Not Spark jobs. Not Docker containers. Meaning. "What is customer churn?" is a semantic question. "Which table stores the churn flag, what Spark job refreshes it?" — that is implementation. Most data architectures make the agent wade through implementation to reach meaning. That is tokens. Real money. Einsteins arguing about USB 2.0 vs 3.0 when someone asked what time the meeting starts. And yes — today's models are surprisingly good at this navigation. The pattern works. Until you have hundreds of data products across an enterprise and the agent isn't resolving meaning anymore — it's guessing. Guessing wrong is silent and expensive. 𝐃𝐞𝐭𝐞𝐫𝐦𝐢𝐧𝐢𝐬𝐭𝐢𝐜 𝐬𝐞𝐦𝐚𝐧𝐭𝐢𝐜𝐬 𝐛𝐞𝐥𝐨𝐧𝐠𝐬 𝐛𝐞𝐥𝐨𝐰, 𝐧𝐨𝐭 𝐚𝐛𝐨𝐯𝐞 In the reference architecture, Knowledge Graph sits at the top — a Core App alongside Analytics Tools and Notebooks. That places semantics at the application layer. IMO, Analytics is a product. Or, family of products. So is Activation. Maybe Knowledge Graph is too — as long as it can participate in the recursive dependency graph where every data product is both input and output. Let us be generous and say it can. But the architecture is drawn as a stack. Stacks flow up. Data Products compose laterally and recursively — churn depends on customer events, which depends on a semantic definition of "customer," which depends on identity resolution. That's a DAG, not a layer cake. And if your semantic definitions live at the top of the stack, every layer below them is flying blind. Deterministic semantics — the layer that resolves meaning before anything else runs — belongs below, not above. It should be the foundation the stack stands on, not a feature bolted on at the top. Semantics should be the floor, not the ceiling. Continued in comments 👇
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James Corcoran
STAC Research • 18K followers
Few in computer science combine academic depth with real-world impact like Simon Peyton Jones. As co-creator of #Haskell and the Glasgow Haskell Compiler, his work has massively impacted how we think about and implement safe, expressive, high-performance software. Haskell’s strong static type system and expressiveness make it especially valuable in financial services, where correctness, reliability, and maintainability are paramount. It underpins quant systems, core banking, exotic instrument pricing, risk analytics, and real-time transaction processing at many of the world’s largest financial institutions. Firms like Barclays have developed domain-specific languages in Haskell for their derivatives businesses. Standard Chartered maintains a major Haskell codebase for its markets infrastructure, crediting the language with improved structure and earlier error detection. A new trend is also emerging, as developers combine functional programming with hardware engineering, especially through #FPGAs, to achieve ultra-low latency in high-frequency trading. Tools like Clash—a functional hardware description language built in Haskell—are enabling this shift, and FPGA design firms are adopting it widely. This is fueling a growing community of HFT engineers exploring Haskell + FPGA to push frontier performance. Simon’s contributions have been recognized at the highest levels—he is a Fellow of the Royal Society (FRS) and was awarded an OBE for his services to computer science and education. That’s why I’m thrilled to announce that Simon Peyton Jones will deliver the keynote at the London STAC Summit on October 7th. Register now to secure your spot: https://lnkd.in/eDXiAYnh
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Anand Kumar Maraiya
OptimalAgents.ai • 2K followers
Transforming Text Chaos into Clarity with LangExtract Unstructured text—from clinical notes and legal documents to financial reports and literature—often hides critical insights in messy prose. Enter LangExtract, Google’s open-source Python library that leverages LLMs (like Gemini—and even OpenAI or local models via Ollama) to extract structured information reliably and transparently. ** Why LangExtract Stands Out:** Traceable Output: Every extracted entity includes exact character-level offsets, enabling full transparency and easy validation. Schema-Controlled Consistency: With few-shot examples and controlled generation, outputs remain faithful to a defined schema without drifting. Scalable Across Long Documents: Built-in chunking, parallel processing, and multi-pass extraction offer high recall even in large texts. Interactive Visual Review: Output comes with a self-contained HTML visualization—no more static JSON dumps; you can visually explore and audit extract results. Flexible and Domain-Agnostic: Tailor extraction tasks across domains—medicine, law, literature—with just a few examples; no fine-tuning required. Use Cases That Shine: 1. RadExtract for Radiology: Structured visualization of radiology findings using Gemini 2.5, optimized for medical needs. 2. Medical, Legal, Financial, Literary Analysis: Whether it’s dosages in clinical notes, clauses in legal text, or character-emotion mapping in literature—LangExtract handles it all. If you're battling messy text and need structured, reliable data—whether for audits, pipelines, or analytics—LangExtract offers a dependable, developer-friendly solution. Open-source, auditable, and versatile—this is LLM-powered information extraction built for real-world impact. Ready to dive in? Install it via pip, check their GitHub for examples, and start extracting with confidence. https://lnkd.in/gQXn8zGK Let me know if you'd like help integrating this into your next project!
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