AI-podden

Ted Schönbeck, Nordic CTO, Google Cloud discusses the current and future landscape of AI, emphasizing its ability to perform tasks that typically require human intelligence, with machine learning allowing systems to learn independently. Google, an "AI-first" company since 2016, has integrated AI into products like Maps and Search. Schönbeck highlights recent advancements in large language models and generative AI, particularly the use of large token windows for analyzing extensive datasets and the rise of multimodal AI, which processes diverse data types like text, images, and audio. He also addresses the challenges businesses face in scaling AI, recommending fine-tuned, specialized models over generalized large ones.

This episode features special guest, Tom Sodestrom, AWS Enterprise Strategist, speaking on the latest trends in AI and edge computing. Tom shares his insights on the upcoming trends in the next 5-10 years, including the rise of generative AI, increased data volume and importance, productive edge computing, and digital twins and simulation at scale.

This episode, recorded live, is the second installment of Ather and Mimi's special news updates at Epicenter Stockholm. They discuss OpenAI and concerns about its shift from research to product development, as well as AI advancements in math reasoning by DeepMind and OpenAI’s new "Strawberry" model. The hosts also touch on Sam Altman's Worldcoin project and the intersection of blockchain, crypto, and AI. Autonomous vehicle progress is covered, particularly Uber's partnership with Wave, while an AI safety issue at Sakana AI raises concerns about system control. Lastly, they explore NVIDIA's growth and share a fun AI project predicting pole vaulter Armand Duplantis’ potential record-breaking jumps.

This week, guest host (Sifted's) Mimi Billing and Ather discuss June's AI news updates. Topics include Elon Musk's lawsuit against OpenAI over a nonprofit agreement, Anthropic’s Cloud 3 outperforming ChatGPT and Google's Gemini, and major investments in Anthropic by Google and Amazon. They also cover the EU AI Act's approval, marking the first regulatory framework for AI in Europe, and the UN's resolution on ethical AI development. The resignation of Stability AI’s CEO, Emad Mostaque, is discussed in light of the company's financial struggles. The episode highlights the crowded AI startup landscape and the need for innovation. A quick reminder to everyone of our next live recording at Epicenter Stockholm on September 3rd. Sign up at: https://ai-podden-live-at-epicenter.confetti.events/ invite=896d06ea9ecd5f2d0ac122d4cefa8d50c469  Hope to see you all there!

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 experiment and continuously learn, likening this to being "technology teenagers", and highlights AI's democratisation and the need for a culture of experimentation to solve real business problems.

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" and books "The Beauty of Mathematics in Computer Science" and "Algorithms to Live By."

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 owner. 

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. They also discuss recent AI reasoning research and the need for more efficient training methods.

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 Bishop's AI texts.

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 general intelligence (AGI).