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AI-podden News — 29 Nov

AI-podden

Release Date: 11/29/2023

From NASA to AWS, Sky's the Limit with AI show art From NASA to AWS, Sky's the Limit with AI

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In this episode, Ather interviews Tom Soderstrom, AWS Enterprise Strategist, on his career and insights into innovation and generative AI. Tom shares his journey from Sweden to the US, becoming NASA’s first CTO for IT at JPL, and introducing cloud computing. He emphasises innovation through small, low-risk experiments, or “two-way door decisions,” and the formula of Return on Attention plus Return on Interest leading to Return on Investment. The discussion focuses on the potential of generative AI and the gap between excitement and practical applications. Tom encourages leaders to...

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Hybrid AI Systems: The Future of Intelligent Reasoning show art Hybrid AI Systems: The Future of Intelligent Reasoning

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In this episode, Ather interviews Lele Cau, AI research scientist at MotherBrain, part of EQT Partners. They discuss AI as a system integrating software and hardware for intelligent decision-making. Lele describes MotherBrain’s role in aiding deal professionals with data and algorithms, emphasising the importance of knowledge graphs in large language models (LLMs) for maintaining relationships and entities. Lele highlights the need for hybrid AI systems combining various information sources and explore the future of AI hardware, including quantum computing. Lele recommends the movie "Her"...

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Driving Innovation with AI show art Driving Innovation with AI

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In this episode, Ather meets Caroline Ohlsson, Data & AI Director at Verdane. Caroline explains Verdane's investment in tech-enabled companies and how her team supports them with data and AI. She discusses Verdane's use of generative AI tools like Verdain GPT and Microsoft Co-pilot to boost productivity, and shares examples of AI-driven improvements in code development and sales forecasting. Emphasizing the importance of a solid data foundation and responsible AI practices, she advises companies starting with AI to have a passionate business representatives, a data expert, and an AI...

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LIVE at Epicenter: AI-podden News - May show art LIVE at Epicenter: AI-podden News - May

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In our first ever live recording at Epicenter Stockholm, Ather and Mimi Billing open with Kai-fu Lee's prediction that AI will take 50% of jobs by 2027 and the market's projected growth to $184 billion by 2024. Despite major investments, the profitability of large language models (LLMs) remains uncertain. OpenAI's financial success is noted, but high development costs are a concern. Privacy issues with Microsoft's new AI hardware and Google's challenges with its AI overview feature are highlighted. Ethical concerns arise from Scarlett Johansson's lawsuit threat against OpenAI for voice theft....

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Transforming Finance with AI show art Transforming Finance with AI

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In this episode, Ather interviews Anastasia Varava, Research Lead at SEBX, SEB Banken, about AI in banking. Anastasia's work at KTH and SEB Banken focuses on machine learning, robotics, and AI applications to enhance employee efficiency, decision-making, crime prevention, and customer experience. She discusses data sensitivity, the shift to cloud services, and security measures. Anastasia sees potential in simulating financial markets with AI, combining classical computer science with deep learning, and opportunities for startups. She highlights neurosymbolic systems and recommends Chris...

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The Rise of Large Language Models show art The Rise of Large Language Models

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In this episode host Ather interviews Mikael Huss, co-founder and Principal Data Scientist at Codon. They discuss the evolution of AI, noting the shift from traditional data science to large language models (LLMs) like ChatGPT. Mikael highlights the overshadowing of other AI applications by LLMs and generative AI. They emphasize the importance of deeply understanding business problems before applying AI solutions and the potential of open-source LLMs. The conversation also covers the challenges of causal inference in AI, the need for better explainability, and the future of artificial...

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AI-Podden News - April show art AI-Podden News - April

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This week our guest host, Sifted's Mimi Billing and Ather discuss April's AI developments, including; implications in geopolitics and business, highlighting Microsoft's warning about AI's potential use to disrupt elections in the US, South Korea, and India. They explore China's advancements in AI, the impact of quantum computing on AI development, and recent innovations in human behaviour modeling and reasoning algorithms in large language models. The episode also touches on AI's role in the food and beverage industry, exemplified by an AI-developed coffee blend in Finland, while...

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Redefining Retail with AI show art Redefining Retail with AI

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In this episode, Ather hosts guest Alex Baker, global retail strategist, entrepreneur, and Principal at Nordic Retail Hub. They discuss the evolution of AI in retail, highlighting its shift from backend applications to enhancing customer-facing experiences with technologies like dynamic pricing and personalized promotions. They also explore various AI applications that are transforming retail operations, from supply chain management to targeted advertising via retail media networks. The conversation also touches on AI's broader impact on personal productivity and corporate...

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Automating Quality Assurance with AI show art Automating Quality Assurance with AI

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Ather interviews Vilhelm von Ehrenheim, co-founder and CAIO of QA Tech, discussing the use of AI in automating quality assurance for web applications. Wilhelm details how their AI agents test web functionality to ensure reliability before launch, leveraging large language models for enhanced decision-making. He also addresses the challenges of adapting AI to different platforms and anticipates future AI capabilities in broader applications, including the potential developments towards Artificial General Intelligence (AGI).      

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AI in action: A real-world IT approach show art AI in action: A real-world IT approach

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In this episode, Ather interviews Ramprakash Ramamoorthy, AI director at ManageEngine, who clarifies AI's role as a practical tool for pattern recognition and productivity in IT management, rather than a threat to human jobs. Ram discusses how ManageEngine has integrated AI across their product suite since 2011 to optimize IT operations and customer service, enabling proactive management decisions. He emphasizes the evolution of AI from a hyped technology to a crucial component in streamlining business processes and enhancing decision-making capabilities within the IT sector.  ...

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More Episodes

Let’s start with the company behind chatGPT, OpenAI. No one has missed the last couple of weeks' happenings at OpenAI, where the CEO and cofounder Sam Altman was fired on Friday the 17th and then on Monday evening reinstated as CEO. There have been a lot of rumours of why he was fired in the first place but I think we need to focus on something different. Usually, when you kick out your CEO and cofounder, your investors get a heads-up at the very least. In the case of Open AI, the investors include Microsoft, Khosla Ventures, Andreessen Horowitz, Founders Fund and Sequoia — these are big firms. All of them were kept in the dark. The reason for this is that none of these investors sits on the OpenAI board of directors since the company has a different structure — it is run like a non-profit company. I believe this was set up as a part of safety measures since OpenAI is working on AGI (artificial general intelligence) and if the CEO diverged from the safest path, the board could fire him. So after that TDLR, is this a good way to govern an AI company? Amazon’s new 2 trillion parameters LLM Olympus (double what GPT4 has) puts it in competition with OpenAI, Meta, Anthropic, Google, and others. Earlier this month, I read in Reuters that Amazon is investing millions in training an ambitious large language model (LLMs), hoping it could rival OpenAI, Google and Meta. The model, codenamed “Olympus”, has 2 trillion parameters, sources said, which could make it one of the largest models being trained. OpenAI's GPT-4 model is reported to have one trillion parameters. So, it seems the more parameters the better, however, then I read about this Japanese LLM by NEC, which has reduced the size to “only” 13 billion parameters. This LLM is, which is said to achieve high performance while reducing the number of parameters through unique innovations. This not only reduces power consumption but also enables operation in cloud and on-premises environments due to its lightweight and high-speed. There is this understanding that the better the LLM is at language, the more persuasive it can be and also more innovative. Is this the reason why there is so much work being done on having LLMs taught on specific languages? Samsung AI race over Apple – how will the AI development be visible in our smartphones? https://www.theverge.com/2023/11/8/23953198/samsung-galaxy-ai-live-translate-call Some say that AI-powered features seem like they’re becoming the next battleground for smartphone makers. And Samsung has come out this month with a feature that use artificial intelligence to translate phone calls in real-time, it is calling it “AI Live Translate Call,” and will be built into the company’s native phone app. Samsung says “audio and text translations will appear in real-time as you speak”. But Samsung is not alone, Google, for example, has a suite of AI-powered tools to help you edit and improve photos with its Pixel 8 lineup. Apple is reportedly spending a lot of money every day to train AI, and I have to imagine all that investment will show up in some AI-powered features for iPhones. So, what will this mean for our smartphones?

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