Grzegorz Piechota

The case for GB Cloud The AI revolution will need massive computing capacity to enable it. In this paper Demos ‘ Elizabeth Seger with UKDayOne calls for the next government to invest in sovereign compute - GB Cloud - to develop cost effect and resilient compute. GB Cloud should be a public interest company offering discounted access to the NHS, public services and researchers and start-ups and could have parliamentary oversight and public consultation to ensure it is a trusted resource for the nation. The next will have to pick some targets to stimulate growth. This is a good bet. https://lnkd.in/eg28dipv

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Check out my latest UKTN column!

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Some great points here. I thought 'limitless' was also a really good way of framing the usage for AI systems. If the technology starts to extend into every area of our lives, how can we begin to even imagine ways to ensure its safety? I was at a conference last week which focused on the use of AI in policing, and it was clear the Met Police throughly tested the algorithm underlying its live facial recognition technology - relying on independent advice from the 'National Physical Laboratory'. I'd never even heard of the organisation before so I went and looked it up. Apparently, it is a public corporation owned by the Department for Science, Technology & Innovation (DSIT) and its work is focused on 'developing and maintaining the national primary measurement standards', or 'metrology' - the science of weights and measures. I'm sure that was the right approach in this context, but I guess my point is do we have full confidence that the regulatory landscape for AI as it stands is clearly defined - and whose expertise should even be sought in the first place to ensure systems are safe?

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A useful handbook for quick reference and a reminder to all journalists covering the #US elections to ensure information integrity. This is worth a look. As in absorb this before #election day #journalists #newsroom #misinformation #disinformation https://lnkd.in/g4heDxVP

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Did you know that telco has globally underperformed all other sectors, even during Covid when connectivity was a sought-after commodity? On Monday I attended this intriguing lecture at Pembroke College, Cambridge, part of the BT Group series, delivered by Gabriela Styf Sjöman. If you are interested in telecoms and innovation, I recommend watching this video - it's short (if you skip the Q&A), punchy and full of insights delivered in an accessible way. I'd like to believe that the UK will experience a new roaring 20s of networks, but do watch the video to make your mind up. #telco #telecommunications #telecoms #innovation #connectivity

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Big data research and AI has created competing narratives with one side often lamenting the 'rise of the machines' and another side extolling the amazing things that we can learn with big data research. I never bought into the Terminator view, but have been increasingly frustrated with big data research because it's largely descriptive and once we get beyond the pretty pictures, it just wasn't as satisfying because I wanted to get beyond sentiment... I wanted to test and/or build theory not just look at very very (did I mention very) cool visualizations and trends. Then earlier this year my husband came across a RAG/LLM/NLP tool that didn't talk pish (i.e., addressed the well-known problem of hallucinations in tools like ChatGPT and other AIs) AND didn't require a PhD in computer science to use. LlamaParsing was developed to help organizations sort through their jillions of pages of documentation logically and usefully. But in academic terms, what it allows us to do is big data qualitative research and theory building/fit testing. So, I am really excited to share a piece of research that was just posted online today in Corporate Communications: An International Journal where Stuart and I tested the validity and reliability of this LlamaParsing RAG procedure in theory building and testing big data against a chunky data set related to Scottish independence conversations on Twitter (always Twitter, never X). Spoiler alert... yeah... it worked amazingly well. 😉 Apparently, if you can use R for big data analysis, you do can this (that's what Stuart says... that wasn't my contribution ;) ). https://lnkd.in/d-Wpfwhj

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Misinformation in an #election period comes with a heightened source of caution. With the added influx of #GenAI technology, the ability to disrupt the information ecosystem is inevitable. Really pleased to contribute to Press Gazette on my experience in how to spot #misinformation from #disinformation and #malinformation and how it commonly presents https://lnkd.in/egKkbGQt

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Thanks to John Johnston for the POLITICO Europe London Influence story on the training gap between white PR Professionals and those from BME backgrounds. The Chartered Institute of Public Relations State of the Profession survey showed that white practitioners are: - more likely to have received training in the previous 12 months (81% vs. 74%) - are more likely to have agreed training needs with managers - and are less likely to have had requests for training turned down (36% vs. 47%).   This represents statistically significant gap in the training experiences and opportunities of UK BME PR professionals compared to their white colleagues. Not only is training vital for an individual’s progression, and internal profile, as it can shape how an employer views their ability and seniority, lack of access can impact overall achievements as well as retention - a key point brought up by Matthew Otubu. And based on previous research and people's lived experience, it’s also a red flag for other missed work opportunities and unspoken barriers to fairness and inclusion. Sadly the training gap is not surprising but it is unacceptable and, in an age of skills shortages, inexcusable. #PR #Comms #DiversityandInclusion #Training https://lnkd.in/eCZypZM8

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Taking a step back from local politics in the UK today, to focus on what's actually going on in wider markets. A great rotation is underway, with super-modern-AI-picks'n'shovels-play Nvidia now in a bear market from its most recent high, while the neglected detritus (the apparent view of many in the market) that makes up the Russell 2000 has swirled nearly 12% higher over the same period. Will this continue? The latest missive from Vincent Deluard, CFA caught my eye on this point. He sees echoes of the 2000 dotcom bust in today's AI bust, but with three key differences which could mean that the scale and length of any correction is limited. https://lnkd.in/gqrvj9WQ

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After OpenAI raised $6.6bn last week, I wrote for the Financial Times Lex column about the increasingly difficult lifecycle of the unicorn. There are around 1,500 private companies worth $1bn, but few reach real scale - which Bain & Company defines as $10bn of revenue and $1bn of cash flow. The likely reason is that founders are getting easy money from pumped up VCs without having to show proper business skills. But some folks in Silicon Valley (including many founders themselves) take the opposite view: that the real unicorn-killers are management-think and corporate governance police. https://lnkd.in/eWtYnq45

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This is an interesting analysis from Reuters Institute for the Study of Journalism on how AI chatbots responded to questions on the UK #GeneralElection. It's particularly pleasing to read about the positive impact of Full Fact in providing much needed context to false or misleading claims. "Our preliminary investigation into AI chatbots’ responses to questions about the upcoming UK general election revealed a mixed performance. While we received some accurate and well-sourced answers, especially to fairly basic questions with simple factual answers, there were also instances of partially correct or false and misleading information. These inaccuracies highlight the need for caution when relying on chatbots for election-related queries." https://lnkd.in/dReZWEJn

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https://lnkd.in/e_XyCc3X A corking little #research based #PR story showing how businesses can create headlines by mining thier own data and putting a value to it…

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With the countdown on for the #UK general #election on 4th July, we’re pleased to present the latest edition of 'Let's Vote', where we explore the key battleground issues, Labour's economic plans, the latest opinion polls and much more: https://lnkd.in/esnnTb7P #Politics

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Nearly half the world's population goes to the polls this year, including us in the UK. It's also the first big election season - Indian, Mexico, US, UK, EU - since generative AI tools have been really widely available. After years in which mis and disinformation has disrupted and reshaped our democracies, the stakes are now even higher. The team at Demos have been thinking about what could practically be done to help protect democracy. It's too late in the UK for meaningful legislation (the Online Safety Act took five years and ended up a shadow of what it originally promised), the tech companies are working on watermarking and tracking AI generated content but the technical solutions aren't good enough yet. What's left for immediate action? We're calling on the UK political parties to come together to agree how they will use generative AI at the election in order to model best practice and start to shape the norms of what's acceptable use. This is me talking about it on the radio yesterday with Jimmy Wales, founder of Wikipedia, who, along with a wide range of experts and leading voices are backing our call. Working with the brilliant Full Fact we have drafted an oven-ready agreement the parties should sign up to committing to: • Not using generative AI to create deepfakes designed to mislead • Labelling where they are using generative AI to improve transparency and trust • Not amplifying content they suspect could have been created using generative AI • Giving their campaigners guidance on how to use generative AI responsibly.... It won't solve the bigger problem of malicious actors and state interference, but it will start to show world class leadership in this area... Read the full agreement here: https://lnkd.in/eW7YEdeh Read our briefing paper by the brilliant Elizabeth Seger here: https://lnkd.in/eYH7HFzM

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🚀 How is AI transforming the media, journalism, social media and brand engagement? Dive into our latest FIR Interviews podcast, where Shel Holtz, SCMP, and I interview Pete Pachal, founder and CEO of The Media Copilot, to explore the evolving landscape of AI in these fields. Pete shares how generative AI is not just a tool but a transformative force in content creation, research, and brand engagement. We discuss the potential of AI-driven chatbots and platforms like Maven, which prioritise meaningful conversations over traditional metrics like likes and follows. Pete also offers predictions for the next 3-5 years, where AI could redefine how we interact on social media, with an emphasis on filtering and summarising content. 🔹 We discuss how ethical guidelines are crucial to managing AI's impact on misinformation, and how the future of social media engagement will be driven by AI that will make interactions more substantive and personalised. 🎧 Tune in to a must-listen conversation for communicators, media professionals, and brands looking for insights into how to stay ahead in the AI era ⬇️ #AI #brandengagement #podcast https://lnkd.in/egU35qnz

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The impacts of the strengthening blizzard of noise/misinformation mean corporate decision makers are increasingly reliant on trusted sources to inform their future direction. Day in day out the FT delivers a level of accuracy that meets this requirement.

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Artificial intelligence is transforming the media landscape, but with great power comes great responsibility 🧑‍💻 🤔 How do you think we can mitigate the risks of misinformation and bias in AI-generated content? #AI #Journalism #MediaEthics

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