Foreign
Demystifying Frequently Asked Questions on Artificial Intelligence
On Artificial Intelligence: The Podcast, we dive deep into the latest AI trends. Join us as we explore groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From chatGPT to the recent merger of Google Brain and DeepMind, we will keep you updated on the ever-evolving AI landscape. Get ready to unravel the mysteries of AI with us.
In today’s episode, we’ll cover the productization of large language models (LLMs) as cloud services, the projected wealth generated by AI in 20 years, and the top-earning companies. We’ll also discuss Microsoft’s focus on the new AI platform shift and the limitations of GPT models. Additionally, we’ll explore the potential negative impact of AI girlfriend apps and various developments and implementations of AI technology by companies such as Ridgelines, BMW, MIT, Microsoft, Alibaba, OpenAI, Netflix, Nvidia, and Spotify. Finally, we’ll delve into the use of the Wondercraft AI platform to create podcasts with hyper-realistic AI voices.
AI is becoming ubiquitous and versatile, leaving many of us feeling both intrigued and apprehensive. But what’s next for these large language models? Well, they’re set to become generative as a service (GiaaS) cloud products, just like other as-a-service offerings. The big players in cloud computing, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), will develop, partner with, or acquire generative AI capabilities to offer services. Think of it as an expansion of their existing cloud ecosystems. Google has already invested in the generative AI race, and AWS isn’t far behind. IBM, with its long-standing expertise, is also a key contender. Microsoft, however, seems to be leading the pack. These companies will create vast ecosystems around their generative AI tools, much like there are ecosystems around enterprise infrastructure and applications.
To effectively apply LLMs, companies will need to make decisions about which tool to use and how to leverage generative AI across various functions and industries. They will refer to documented use cases and metrics like ROI, OKRs, KPIs, and CMM to determine the best approach. Once the internal due diligence is completed and promise is seen, they’ll move forward with the implementation phase.
According to Stuart Russell, a computer science professor at the University of California, Berkeley, and co-author of the AI textbook used by over 1,500 universities, AI is predicted to generate about 14 quadrillion dollars in wealth in the next 20 years. The top five AI companies are set to grab a big slice of that pie. Google is expected to bring in 1.5 quadrillion dollars, Amazon 1.1 quadrillion dollars, Apple 2.5 quadrillion dollars, Microsoft 2.0 quadrillion dollars, and Meta 0.7 quadrillion dollars. However, these companies are paying significantly less in taxes than they used to. This raises the question of whether we should prioritize the millions of people who could lose their livelihoods to AI or align more with the top AI companies enjoying their lower tax rates.
While the initial estimate of three to five million job losses might be incorrect, there is still a concern about the potential loss of jobs to AI. It’s crucial to find a middle ground that is fair and caring. We need to align our values with the impact of AI on our society.
ChatGPT and other large language models gain their linguistic capacity through training but do not possess consciousness or personal identities. Their responses are based on patterns learned from data rather than true understanding. AI girlfriend apps, on the other hand, raise concerns about potential negative effects, such as reinforcing harmful gender dynamics and leading to gender-based violence. While these apps are gaining popularity, it’s important to consider the long-term impacts and potential risks.
In other AI news, Ridgelines, a subsidiary of Fujitsu in Japan, has developed an AI system capable of voice communication with humans. BMW has utilized AI to cut costs at its factory in South Carolina. MIT has introduced a technique called Photoguard to protect images from malicious AI edits. Microsoft is making advancements in natural language interfaces with its TypeChat Library. Researchers have proposed three DLLMs that inject the 3D world into language models. Alibaba Cloud has become the first Chinese enterprise to support Meta’s open-source AI model, Lama. OpenAI’s ChatGPT for Android is expanding its availability. Netflix is looking for an AI product manager. Nvidia is making its DGX Cloud widely accessible on Oracle’s infrastructure. Spotify’s CEO suggests exciting possibilities for AI-powered capabilities within the music streaming platform. Finally, CoHere has released Coral, an AI assistant designed for enterprise business use.
If you want to dive even deeper into the world of artificial intelligence, check out Etienne Newman’s book, AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence. It’s available on Shopify, Apple, Google, and Amazon. This book is an essential read for both AI newbies and seasoned enthusiasts, providing expert insights and expanding your knowledge and understanding of AI.
Thanks for listening to today’s episode. Stay tuned for more exciting updates in the world of artificial intelligence!
