AI-podden

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).

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 acknowledging the technological hurdles in mimicking human sensory experiences.

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 efficiency, underscoring the technology's potential to augment human capabilities.

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).

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.

This week our guest host, Sifted's Mimi Billing and Ather discuss March's AI developments, including; Elon Musk has sued OpenAI, alleging violation of their nonprofit agreement through a Microsoft collaboration and deviation from open-source values. Concurrently, Musk introduced his open-source language model, GROK. Meanwhile, Anthropic's new AI, Cloud 3, reportedly surpasses ChatGPT and Google's Gemini in performance. The episode also covers the EU AI Act and a UN AI resolution, drawing varied perspectives on their impact. Additionally, the resignation of Stability AI's CEO and the company's financial woes post a $101 million October 2022 funding round were discussed, underlining the difficulties in AI monetization and the saturated startup landscape.

This week our guest host, Sifted's Mimi Billing and Ather discuss February's AI developments, including OpenAI's new video tool, Sora, and its careful release strategy amidst ethical concerns. They explore the bias issues in Google's Gemini AI and contrast different AI philosophies, highlighting the debate between practical AI applications and the pursuit of genuine intelligence. The conversation also covers NVIDIA's significant market valuation, the concept of an AI bubble, and Google's approach to AI-written content for publishers. Investments in robotics by NVIDIA and OpenAI are mentioned as forward-looking strategies. Finally, the hosts ponder the hype around AI compared to past excitement in the crypto industry. Don't forget to subscribe and follow us on Linkedin.

Salman Avestimehr, USC professor and FedML co-founder, discusses AI, federated learning, and large language models. This week's topics include; AI definition, distributed and federated systems research, current challenges in generative AI, and trustworthiness in ML. Ather and Salman explore the future of accessible LLMs on personal devices, stress the importance of data, and discuss challenges like distinguishing machine-generated outcomes. The conversation touches on enforcing regulations in the era of open-source tools and recommends the book "Life 3.0" Don't forget to subscribe and follow us on Linkedin.