AI-podden

In this episode of the AI Podcast, host Ather Gattami interviews Michal Sustr, co-founder of EquiLibre, a company that uses game theory and reinforcement learning for trading. Michal discusses the company's approach to trading, which is based on the idea that markets can be modelled as games. He explains that EquiLibre uses game theory to develop algorithms which can predict the behaviour of other traders and make profitable trades. Ather and Michal also discuss the future of AI, and Sustr predicts that large language models (LLMs) will continue to be a major area of research in the coming years. Michal believes that LLMs will eventually be able to reason and solve problems in a way that is indistinguishable from human intelligence. Don't forget to subscribe and follow us on Linkedin.

Reinforcement learning is a type of machine learning that allows agents to learn by interacting with their environment. DeepMind researcher, David Abel is interested in using reinforcement learning to understand and build intelligent agents. One of the big questions in AI is what exactly "intelligence" is. Another big question is how to build intelligent agents that can reason and solve problems. Abel believes that it is important to achieve conceptual clarity in AI. Abel's research focuses on AI's core scientific questions, emphasizing the need for conceptual clarity about intelligent behavior and agents. David express skepticism about creating AI with certain reward functions, suggesting that multi-criteria objectives could better align AI with human interests. Don't forget to subscribe and follow us on Linkedin.

In this episode, Mimi and Ather delve into the impact of AI on elections and political communication as well as deepfakes and cybercrime. They address OpenAI's suspension of a developer for creating a politician-impersonating chatbot and an AI-generated robocall falsely imitating President Biden, demonstrating AI's potential misuse in politics. They also discuss McAfee's Project Mockingbird, an AI technology introduced at CES 2024 to combat deepfake audio and cybercrime. Additionally, the episode covers The New York Times' lawsuit against OpenAI, highlighting the intricate legal and ethical issues surrounding AI-generated content in the realms of copyright and media. Don't forget to subscribe and follow us on Linkedin.

Edward Hu, Researcher at OpenAI, known for his invention of LoRA, a widely used machine learning method to fine-tune Large Language Models (LLMs) which he co-invented at Microsoft, shares his views on LoRa. Together with Ather he also discusses the development of GFlowNets as a promising tool for the development of reasoning and planning AI systems. Don't forget to subscribe and follow us on Linkedin.

Mimi Billing, European editor at Shifted and Ather highlight the latest news in AI in December and take a look back at 2023. In this episode, you will hear the latest on the release of Google DeepMind's Gemini in its Ultra, Pro, and Nano versions. How European Union policymakers have reached a provisional agreement on AI rules under the EU AI ACT. Additionally, the episode also cover developments in robotics, provides a review of AI in 2023, and offers predictions for what we might see in the field of AI in 2024. Don't forget to subscribe and follow us on Linkedin.

Andy Karvonen, Prof. of Urban Design and Planning at Lund University talks of the "Urban Brain", where we have some kind of smart city control room managing all aspects, from traffic to transportation and the management of facilities. Andy and Ather discuss the pros and cons of such a future, delving into the hard but important questions of privacy, surveillance, and so on. Andy and Ather also discuss the future of an AI-driven society, policymaking, and how to deal with the challenge of big tech dominating in the AI tech field. Don't forget to subscribe and follow us on Linkedin

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 shares with us her thoughts about the "AI hype" and the trends of AI startup investments. She describes the ultimate startup settings where she would be interested in investing. In particular, Nastaran expresses her interest in ideas where AI could help us solve climate challenges and be more sustainable, and she provides a couple of examples. Beyond the idea, Nastaran's focus is on the team and the passion of the team to solve the problems they are tackling. What makes female-founded AI startups different? This is a question that Nastaran answers. While her observations don't show any difference between companies with and without female founders, she notices that female founders tend to focus on sustainability. Ather asks Nastaran whether she would ever invest in an AI company based on a presentation only. Tune in to hear Nastaran's thoughts! Don't forget to subscribe and follow us on Linkedin.

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.

We have great pleasure of hosting Mert Pilanci, Professor at Stanford University. Mert Pilanci shares with us his recent research breakthroughs in machine learning. Mert and his group discovered that the training of shallow neural networks can be transformed into super-efficient algorithms that always achieve the best accuracy possible on the first shot. Read more: https://ai-podden.se/

We are excited to host Anders Arpteg this week, Data Science Director of the Swedish Security Service. Anders shares with us the very important role he and his team play in protecting Sweden from bad actors with the help of data and AI! Find more: https://ai-podden.se/

Our guest in this episode of AI-podden is Milan Kordestani, Entrepreneur, Investor, and Author. Milan, who is a serial entrepreneur, tells us about how a couple of his startups apply AI to help people prepare for interviews and provide training and mentorship to help them choose individualized career paths. Milan puts his investor hat on and explains his view on the investment market. He believes that simply applying AI without a technological moat won't be attractive enough for investors. Milan and Ather also discuss Milan's book "I'm Just Saying,", where the issue of not being able to have open conversations about different opinions is becoming more of a challenge today. This is highly relevant today as we debate the dangers and advantages of AI in the future. Read more: https://ai-podden.se/

In this episode, we are hosting two great guests, Reggie Townsend, Vice President, Data Ethics Practice. Member of the Biden AI Advisory Committee, and Josefin Rosén, Head of AI at the SAS Institute. We discussed broadly how we can benefit from the technology of artificial intelligence and at the same time make sure that it's used for the benefit of mankind, as well as what measures we should take to prevent the malicious use of AI. Read more: https://ai-podden.se/

AI-podden with Stephanie Ora and Mark Thundercliffe, SAS Institute. Stephanie and Mark discuss the role of AI, data, and analytics for risk management. We get some examples of how AI could be used to mitigate risks such as fraud and money laundering in financial services. Read more: https://ai-podden.se/

In this episode, AI-Podden talks with Anders Gustafsson, Chief Strategy Officer, Brightbid. Anders tells us how Brightbid uses AI to help companies better reach their customers through Google Ads. He explains how Google and Bing ads work and how a more data driven approach to bidding per ad and user could increase the conversion rate, that is increase the number of users clicking on a company's ad per amount of money spent. Read more: https://ai-podden.se/

AI-podden with Dylan Sellberg, Director of Product at Hubspot. Dylan tells us about Hubspot's latest AI developments, especially the new product development he is leading, ChatSpot.ai. He also shares other functionalities where Hubspot implemented AI to improve the product. Read more: https://ai-podden.se/

Noam Slonim, Distinguished engineer and Initiator and leader of the Debater project, IBM Noam Slonim shares with us his best boughts on the recent developments of large language models (LLMs)and we discuss how this new technology relates to his previous breakthrough on building an AI that can debate humans successfully and without false claims. Read more: https://ai-podden.se/

Our guest in this episode of AI-podden is Jörgen Warborn, who is a member of the European Union Parliament. Jörgen shares what happens behind the curtain regarding boosting the investments in AI within the EU, but also what happens in terms of regulations. Read more: https://ai-podden.se/en

AI-podden med Jim Dowling, Founder and CEO of Hopsworks and Associate Professor in Computer Science at KTH Read more: https://ai-podden.se/en

In this episode of AI-podden, we are hosting Ted Persson, Partner at EQT Ventures who has also a long journey of being an entrepreneur. Ted shares with us the recent developments within Venture Capital in the field of AI, telling us about EQT investments but also about other startups that are doing AI which he finds interesting. We discuss the recent developments of Large Language Models and image generating tools and where we can see the value of such tools. Read more: https://ai-podden.se/

In this episode of AI-podden, we are happy to host Daniel Akenine, National Technology Officer at Microsoft Sweden. Daniel tells us about some of the recent AI updates to Microsoft products, and how the recent developments of OpenAI's ChatGPT will be used. The new solution that Microsoft will roll out is a tool that will take meeting notes and summarize them, based on a meeting recording for instance. Another tool will help sales to handle the flow of the sales process to boost the customer relationships. Read more: https://ai-podden.se/

AI-podden's guest in this episode is Sebastian Krakowski, Professor at the Stockholm School of Economics and Digital Affiliate at Stanford University. Sebastian conducts research at the intersection of behavioral science, economics, and AI. Sebastian tells us about his studies on the importance of personalizing AI tools to their users, and how his studies show that it could have a negative effect on the performance of users of AI if the AI system itself is not fit to the user's personality, for instance. Read more: https://ai-podden.se/

Our guest in this episode of AI-podden is Sid Khullar, Senior Director of Machine Learning R&D at Northvolt. Sid shares with us some of the interesting machine learning projects currently conducted at Northvolt towards improved battery technology. Read more: https://ai-podden.se/

Our guest for this episode is Kobra "Farzaneh" Etminani, Associate Professor in Machine Learning at Halmstad University. Farzaneh shares with us her research on Machine Learning for Healthcare applications and the recent progress in the field of Machine Learning that she sees promising. In particular, she is very optimistic about large language models such as GPT (Generative Pre-Trained Transformer). Read more: https://ai-podden.se/

AI-podden's guest this week is Erik Brandt, Chief Data Scientist at Shaarpec. Erik shares their work in healthcare where they use AI for more efficient systems to better allocate resources and free up time for doctors to do less administration to help more patients. Erik tells us how we can use AI to help doctors automatically summarize their notes and examinations in documents, instead of doing it themselves. Read more: https://ai-podden.se/

In this episode, we are hosting Moha Bensofia, CEO of Mendi, a startup that provides cutting edge brain-health technology to help people measure, control, train, and improve their brain function. Read more: https://ai-podden.se/

AI-podden's guest in this episode is Rasmus Adler Wahlberg, Co-founder and CEO of Multiply. Rasmus is a serial entrepreneur, who has spent the last couple of years on Multiply, developing a collaborative product were users can create templates and content with help of AI, that can be shared between team members within a company. Read more: https://ai-podden.se/

We have the pleasure to host Olof Hoverfält in this episode, who is Strategy & Business Design Principle at Reaktor. Olof talks about how they developed the online course "Elements of AI" together with the University of Helsinki, why they did it, and how many that have completed the course so far. Read more: https://ai-podden.se/

Fredrik Hofflander, Head of AI på Afry, gästar AI-podden och berättar om hur man ska göra för att få in AI och i ett företag. Fredrik ger råd på hur man ska hantera utmaningar med kompetens, och menar att man ska börja med att titta närmare på företagets behov och förstå vad exakt man försöker optimera eller förbättra, och på så sätt hitta rätt kompetens för att lösa problemen. Läs mer: https://ai-podden.se/

Jan Dernestam, Managing Partner på Mannheimer Swartling I denna live-inspelning gästas AI-podden av Jan Dernestam, Managing Partner på Mannheimer Swartling, som diskuterar AI inom juridiken. Läs mer: https://ai-podden.se/

I detta avsnitt gästas AI-podden av Alexander Hübel, partner och Chief Strategy Officer på Turbotic. Alexander berättar om hur Turbotic hjälper företag med att sätta upp processerna för AI-projekt på företag på ett automatiserat sätt. Utöver automatiseringen, så saknas det generellt struktur för hur AI-projekt ska bedrivas då det är båda nytt och komplext. Alexander och Ather diskuterar vidare svårigheterna med att få in AI i en organisation, och framför allt när erfarenhet saknas i styrelsen och/eller ledningen. Alexander ger förslag på hur man ska gå tillväga och ger allmänna råd utifrån sin egen erfarenhet och vad han tror kan vara ett sätt att ta sig an denna utmaning. Läs mer:https://ai-podden.se/

Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge, Senior AI Fellow at the Alan Turing Institute, visiting Professor at the University of Sheffield and the co-host of the podcast Talking Machines. Read more: https://ai-podden.se/

AI-podden is happy to host Pelin Ozbozkurt, Data Science Solution Director at Oracle. Pelin shares with us some of the interesting projects they have been working on at Oracle. The first one is on fraud detection which is an anomaly detection problem that is challenging because of the fact that fraud doesn't happen that often which makes the data small. Pelin describes how they use other fields to tackle this problem. She mentions in particular the help of human supervision which is vital in building good predictive models. We also make the connection between this methodology and one of our previous guests at AI-podden, Gary Marcus, who wrote in his book "Rebooting AI" the importance of having a new fresh take on AI and not only rely solely on Deep Learning. What's interesting is that Pelin mentions the development of unsupervised learning as one of the most interesting fields to explore within AI research. More interesting topics are discussed in this episode! Read more: https://ai-podden.se/2020/11/ai-med-eller-utan-mansklig-overvakning/ Download Oracle Analytics for Dummies for free here>> https://go.oracle.com/LP=103205?elqCampaignId=261794

In this episode, Noam Slonim, the project leader of the IBM Debater project tells us about their journey to build AI that can perform a debate on a human level. Noam Slonim and Ather Gattami discuss the challenges of the project and what needed to be overcome, the role of human emotions in debates, and how the AI debater could be improved in the future. Don't miss out on this super interesting story! Read more: https://ai-podden.se/

The AI-podcast proudly hosts Professor Stuart Russell, University of California at Berkeley. Professor Russell is one of the pioneers of AI and his over 1000 pages book "Artificial Intelligence: A Modern Approach", co-authored with Peter Norvig, is a standard reference in the field and you find on the shelf of any serious AI expert or practitioner. Professor Russell recently released his new book "Human Compatible", which discusses the risks of AI and how we should think to build Intelligence that serves humanity. In this episode, we discuss this very interesting topic and other topics. Professor Russell shares his experience and gives great insight into the future of AI and where we will see it happening with great impact in the coming 5-10 years.

Ather Gattami har bjudit in Åsa Zetterberg till ett specialavsnitt av AI-podden med anledning av COVID-19. Åsa Zetterberg är förbundsdirektör på IT & Telekomföretagen och berättar om deras initiativ till uppropet #Vitecherupp som vill lyfta goda exempel på hur IT och digitala tjänster kan hjälpa samhället just nu. Ather och Åsa pratar om hur uppropet kom till och hur man kan få fler företag att i branschen att sluta upp bakom #vitecherupp. Åsa vill även belysa att vi i Sverige gynnas av att vi kommit så pass långt som vi har inom digitalisering.

In this episode of our AI podcast "AI-podden", we talk to Gary Marcus, the author of "Rebooting AI" and Founder of robust.ai. We discuss the state of AI, what we have achieved so far and what AI cannot do today. Gary underlines the fact that we are far from so called Artificial General Intelligence (AGI) where computers have cognitive abilities that match the humans. He argues that Deep Learning alone will most likely not solve the problem and that we need to use tools from other fields within AI and combine them with Deep Learning in order to get closer to AGI. Gary reasons around the danger of AI, and discusses why he thinks that an AI that could be a direct threat to the human race is not likely to happen in the next decades. Läs mer: https://ai-podden.se/

Veckans AI-podden gäst är Pin-Yu Chen, Chief Scientist på IBM Watson Research. Pin-Yu berättar om hur AI har utvecklats och hur fokus har skiftat från att göra noggranna produktioner till att rekommendera och även ta beslut som är av stor vikt eller spelar avgörande roll i en process. Han nämner exempel från egna forskningen i området säker och robust AI teknologi. Exempel på sådan beslut är att döma i juridiska processer, att ta beslut i vilka man anställer eller gör sig av med, eller utbildningssystemet som t ex att använda sig av AI för att rätta antagningsprov på universitet. Därför är det viktigt att bygga AI system med andra mål än noggrannhet som rättvisa, jämställdhet, jämlikhet, osv. Pin-Yu understryker också vikten av att kunna förklara besluten som tas eller rekommenderas av AI system. En annan aspekt är robusthet mot extern påverkan, som där en liten ändring i det datat man matar in inte ska leda till förödande beslut. Vi diskuterade även hur IBM har transformerats på senare år inom AI forskningen där man nu är mycket mer öppen med forskningsresultaten i form av publikationer och open source metodik. Pin-yu förklarar att konkurrensen är så hård att även jättar som IBM måste öppna upp så att man lockar till de bästa talangerna. Detta är säsongens sista avsnitt! Läs mer: https://ai-podden.se/

AI har idag en viktig rådgivande roll inom handel av aktier, inte minst när det kommer till robothandel. Veckans gäst i AI-podden är Mike O'Rourke som arbetar som Head of AI på Nasdaqbörsen i New York, en arbetsplats som satsar på AI och med många framgångsrika tillämpningar inom området. Mike O'Rourke förklarar bland annat hur AI kan användas för att hantera stora datamängder och se samband som människor inte kan se på grund av mängden komplex information. Nasdaq arbetar också med AI för att upptäcka olagliga aktiviteter inom börshandel. Det kan handla om aktörer som på olika sätt manipulerar priser för att tjäna så mycket pengar som möjligt på prisändringarna. Mike O'Rourke berättar även hur Nasdaq använder sig av transfer learning som innebär att man tar med sig lärdomar från Ai algoritmer inom ett område och applicerar dessa på ett annat. Allt för att lösa liknande problem där data kanske saknas. Läs mer: https://ai-podden.se/

Veckans avsnitt av AI-podden gästas av Matilda Ernkrans, minister för högre utbildning och forskning. Ather och Matilda pratar om hur Sveriges regering vill satsa på AI, varför det anses viktigt, och vilken samhällsnytta regeringen tror det kan bidra med. Tillsammans diskuterar de om AI är en teknologi som kommer avgöra länders framtida ekonomi och välstånd och resonerar kring hur regeringen kan agera – inte minst eftersom många hävdar att AI är den nya elektriciteten. Matilda berättar om hur Sverige satsar på att bygga AI kompetens idag och vad regeringen gör för att driva AI forskningen i Sverige framåt. De diskuterar även hur man genom politik kan försöka tillse att AI inte används till ändamål som är ogynnsamma för mänskligheten. Ather och Matilda pratar även om det faktum att Sverige ligger efter när det gäller AI. Hur ska man säkra Sveriges konkurrenskraft? Varför tror man att ett land som Kanada ligger så långt före oss? Det är några frågor som vi får svar på i veckans avsnitt. Läas mer: https://ai-podden.se/

I veckans avsnitt av AI-podden pratar Ather Gattami och Anna Ringborg om "Deep learning"-algoritmer som kan vara förvånansvärt enkla att manipulera. I mars 2018 visade kinesiska forskare att de lyckats attackera en Teslabil genom att på flera sätt lura deras algoritmer. Genom att förändra den data som matats till bilens sensorer kunde forskarna förvirra den artificiella intelligensen som körde bilen. AI och deep learning ses som nästa stora militära slagfält. AI kan till exempelvis användas hos drönare och i system för analys av satellitbilder eller när man avlyssnar kommunikation. Men som Tesla-hacket visar, kan en fiende som vet hur en AI-algoritm fungerar göra den värdelös eller till och med vända den mot sin ägare. I podden diskuterar Ather och Anna även hur datorer kan använda radiovågor för att se rörelser bakom väggar och i mörker. De pratar också om det amerikanska rättssystemet och hur domare får hjälp av AI-tjänster för att avgöra huruvida en åtalad ska vara frihetsberövad eller släppas fri i väntan på rättegång. Läs mer: https://ai-podden.se/

Ett av de största problemen för att företag ska bli mer AI-drivna är att hitta rätt kompetens. Men det finns fler ingredienser som företag bör tänka på för att bli mer effektiva. Stora företag måste utvecklas med sin tid och se vilka möjligheter AI kan ge verksamheten för att inte riskera att bli utkonkurrerad av en mer effektiv uppstickare på marknaden. Nya företag som helt och hållet har fokuserat på en AI-lösning för ett befintligt problem skapar en helt ny affär med just den edgen. Historiskt finns det flera exempel på företag som har blundat för den teknologiska utvecklingen och gått under. Det är ingen slump att AI har fått så mycket uppmärksamhet den senaste tiden. Det sägs bland annat att AI är den nya elektriciteten och teknologin kommer ge upphov till nya möjligheter man inte har sett innan. Man kan se AI som en ny infrastruktur som kommer påverka många olika delar av samhället. Från ekonomi och finans till marknadsföring och medicin för att nämna några aktuella exempel. I AI-podden får du ett recept på de grundläggande stegen man som företag behöver tänka på när det är dags att ställa om till en mer digital verklighet.

Är datorer kreativa på riktigt? Idag kan datorer på ett enkelt sätt omvandla ett fotografi till en målning i stil med stora konstnärer som Picasso eller Van Gogh. Datorer kan skriva och komponera musik. AI-Podden har bjudit in Professor Arthur I. Miller som är aktuell med boken "The artist in the machine" för att diskuterar huruvida maskiner faktiskt är kreativa eller om de används som verktyg av den kreativa användaren. Symbolisk AI kan producera konst som är kännbart för det mänskliga ögat som konst. Men det är konst som har förprogrammerats med hjälp av den data som man har valt att mata algoritmerna med. Det finns inga överraskningar. Harold Cohens Aaron AARON-algoritm producerar ganska vackra målningar med mallar som har programmerats in i den. På liknande sätt programmerar Simon Colton vid Goldsmith's College i University of London "The Paint Fool" för att skapa en bild av en sitter i en viss stil. Men ingen av dessa hoppar någonsin utöver dess program. Till skillnad från symboliska algoritmer är Artificiella neurala nätverk mycket mer experimentella och oförutsägbara. Nätverken kan lära sig själva vilket gör att arbetet utvecklas utan något mänskligt ingripande, därför kan man också säga att de är mer verkligt kreativa. Ett neuralt nätverk är Alexander Mordvintsevs Deep Dream som skapade mardrömsbilder från invändiga neurala nätverk(ConvNets). Ett annat exempel är Ian Goodfellow's GAN (Generative Adversarial Network) som fungerar som en domare för sina egna skapelser, och Ahmed Elgammal's CAN (Creative Adversarial Network), som skapar stilar av konst som aldrig sett förut. Alla dessa genererar mycket mer utmanande och svåra verk som är maskinens egen uppfattning om konst, inte människans idé om vad konst är. I stället för att vara ett verktyg, deltar maskinen i skapandet.