Mika Gustafsson, Prof., and David Martinez, PhD student, both at Linköping University conduct research in Bioinformatics and precision medicine. They are exploring how to use complex patient data, both clinical and environmental (such as the lifestyle) to develop personalized treatments and to help understand diseases more in depth in order to take preventive measures. David and Mika explain why bioinformatics and precision medicine is so complex, given the number of parameters affecting the human body and their complex interplay. The challenge of data acquisition is another challenge. For that challenge, they are working on federated learning to train AI systems without requiring private data to be shared. Ather, Mika, and David discuss the trade-offs of using federated learning, and the performance degradation that one might get for not sharing the data to a central unit directly. David and Mika go on and tell us about the greatest impacts of AI on medicine in the near future, from personalized medicine to helping less wealthy countries.  Don't forget to subscribe and follow us on Linkedin.

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? Don't forget to subscribe and follow us on Linkedin.

Agnes Lindell, Head of Data Driven Business at Elvenite shares her experience in building data driven tools in the food industry, all from some of their most successful use cases to how they managed to do it. She mentioned the biggest challenges and how they managed to tackle them. A few examples include inventory optimization with over 10% of savings, to using AI to efficiently grow various types of seeds in different environments. Agnes Lindell walks us through simple steps that she follows in order to become data driven and check the AI readiness, that is all from the level of digitalization to the availability of data, checking data quality, starting small to build a proof of concept, etc. She does also share her favorite AI tools (Hint: it's not a Chatbot!).  Don't forget to subscribe and follow us on Linkedin.

Kye Andersson, Co-Founder and Chief Product Officer at Canucci and also author of the recently published Sifted article on the technological, and especially AI gap, between the EU and the US and China. Kye argues that we have too much focus on regulations, especially on less likely scenarios, and we are making the innovation in the EU more difficult. He underlines the fact that there are more urgent topics to discuss when it comes to regulations and societal impacts, rather than the focus of making it extremely difficult to innovate in the field of AI. Kye and Ather discuss how the EU should approach AI developments and regulations, what benefits we may get in the future, and what a future society might look like.  Don't forget to subscribe and follow us on Linkedin.

In this special episode of AI-podden, we have the pleasure to introduce Mimi Billing from Sifted who will be co-hosting AI-podden in this special format where we get updates of the recent AI developments. In this episode, we are discussing why Nvidia is using AI to train a robot how to spin a pen between its fingers, China’s claim that they have built an LLM as good as Chat GPT4 and the newest developments in the space of regulating AI - these are some of the topics discussed in this episode of the AI podcast with Ather Gattami and Mimi Billing.  Don't forget to subscribe and follow us on Linkedin.

The AI Swede of the year (2023) is Max Gordon, and he is also our (returning) guest in this episode of AI-podden! Max is an orthopedic surgeon and Associate professor at Karolinska Institute. Max Gordon shares with us his story of applying AI in Healthcare, how he got into it, where he started, and how he dealt with acquiring data, testing, building the user interface, and having a prototype transforming into a product at Danderyd Hospital where he does his clinical work.  Don't forget to subscribe and follow us on Linkedin.

Nastaran Baleng-Soultani, Co-founder of Space Academy and RadCap Ventures, discusses the AI hype and trends in startup investments. She focuses on investing in startups working on climate challenges and sustainability. Nastaran also explores the use of AI in female-founded startups and the potential of AI for personal productivity. They discuss investor expectations and the importance of solving real problems with unique approaches using AI.

Ather’s guest in this episode is Eva Fors, Managing Director of Google Cloud Nordics. Eva and Ather discuss the most recent developments in the AI services provided by Google Cloud and how Google Cloud is feeling the sentiment around AI developments. Eva shares her thoughts on the balance between AI developments and regulations. She provides examples of what she sees as the biggest challenges with AI. She goes on and compares with the benefits that we could gain from AI. If you want to hear Eva’s conclusions and notifications, don’t miss out on this episode! Don't forget to subscribe and follow us on Linkedin.

 Carl-Axel Wahlström, AI Artist and Creator of the AI fashion magazine Copy hares with us his experience and journey of using AI in his creative work, where he describes the AI tools he is using as “friends” that he enjoys working with. He tells us how he came about to create Copy and the journey that led him to create a magazine that is the first of its kind, with really fascinating images that look so real. Don't forget to subscribe and follow us on Linkedin.

Lars Albertsson, founder of Scling and one of Scandinavia’s most skilled data engineers, with experience from Google and Spotify shares his experience as a pioneer in the data engineering field, what his learnings has been, and the approach he takes in solving data architecture and engineering problems. Don't forget to subscribe and follow us on Linkedin.