In-depth articles with more detailed investigations, interesting thought pieces, and more.
With the introduction of AI-powered search results, the human-generated web is taking a back seat, writes Casey Newton. Google plans to answer more questions directly on the search results page and, according to Newton, is abstracting the web into input for its big language models. The new concept of “let Google do the Googling for … Read more
In his article, author Paul Ford explores the fascinating contradictions of generative AI. He admits that despite its flaws, such as plagiarism, bias, and tendency to spread nonsense, AI holds an irresistible attraction for him. Ford marvels at the shameless way in which AI fills every blank space with information, comparing it to celebrities whose … Read more
The increasing “humanization” of AI systems raises ethical and legal questions. In an interesting article on VentureBeat, James Thomason warns of the downsides of human-like AI. He is particularly concerned about the use of AI in sensitive areas such as therapy and education, where human empathy and understanding are essential. Thomason urges tech companies to … Read more
In his report, “The Economic Impact of Generative AI,” MIT researcher Andrew McAfee examines the potential impact of AI tools on the economy. While generative AI may change some jobs or even make them obsolete, the author predicts an overall increase in the demand for workers, albeit in new occupational areas. Comprehensive training initiatives will … Read more
For four decades, the Cyc project has been working on giving machines the ability to reason. To this end, researchers have built a vast knowledge network consisting of millions of concepts and rules. Cyc can draw conclusions, answer questions, and even reconcile conflicting information from different domains. Despite these impressive achievements, Cyc is largely forgotten … Read more
Although the majority of IT managers worldwide rate artificial intelligence as a top priority, a recent survey shows that most companies are not yet adequately prepared to use it. The main obstacles are a lack of IT infrastructure and unclear guidelines for the ethical use of AI.
Researchers at DeepMind have found that large language models can learn new skills through hundreds or even thousands of examples in the prompt, without the need to fine-tune the model. This method enables companies to quickly prototype and develop AI applications.
And if you want to take a thoughtful, skeptical look at the AI hype, read this article by Molly White. She asks whether today’s AI tools are really worth their cost. And b cost, she doesn’t just mean the monetary cost, but also the environmental impact as well as other potential negative effects on people … Read more
What are AI tools capable of today, and how is the industry evolving? The new edition of Stanford University’s AI Index Report examines these questions in detail. They find that AI is already superior to humans in some tasks, but not all. Meanwhile, most new AI models are coming from companies (51) rather than research … Read more
If you believe the hype, you might think that the world has already fully embraced AI tools. But the reality paints a different picture. Andreas Goeldi explains why at b2venture: The “hype cycle” with its rapid enthusiasm and the actual implementation are not congruent. One of the difficulties for companies is that the benefits and … Read more