ChatGPT, the AI chatbot developed by tech company OpenAI, can find and fix bugs in computer code as well as standard machine learning approaches – and does even better when engaged in conversation.
Dominik Sobania at Johannes Gutenberg University in Mainz, Germany, and his colleagues sought to see how well ChatGPT compared with other AI-powered coding support tools. A number of tools exist that use artificial intelligence to check programming code to ensure there are no mistakes.
A robot made from magnetic particles and gallium can easily change states — making it useful for a broad range of applications in medicine and manufacturing.
In general, we tend to operate on a default assumption that other people are basically truthful and trustworthy. The growth in fake profiles and other artificial online content raises the question of how much their presence and our knowledge about them can alter this “truth default” state, eventually eroding social trust.
Changing Our Defaults
The transition to a world where what’s real is indistinguishable from what’s not could also shift the cultural landscape from being primarily truthful to being primarily artificial and deceptive.
Amazon employees are quickly discovering ChatGPT’s vast potential as a work assistant.
ChatGPT, the eerily intelligent chatbot that blew up since its November release, has been used in a number of different job functions at Amazon, according to internal Slack messages obtained by Insider. That includes answering job interview questions, writing software code, and creating training documents, as Insider previously reported.
One employee said in the Slack channel that the Amazon Web Services cloud unit has created a small working group to better understand AI’s impact on its business. Through testing, this team found ChatGPT does a “very good job” at answering AWS customer support questions, as most answers are based on public information. The AI tool was also “great” at creating training documents and “very strong” in corporate strategy questions.
Connor Leahy from Conjecture joins the podcast to discuss AI safety, the fragility of the world, slowing down AI development, regulating AI, and the optimal funding model for AI safety research. Learn more about Connor’s work at https://conjecture.dev.
Timestamps: 00:00 Introduction. 00:47 What is the best way to understand AI safety? 09:50 Why is the world relatively stable? 15:18 Is the main worry human misuse of AI? 22:47 Can humanity solve AI safety? 30:06 Can we slow down AI development? 37:13 How should governments regulate AI? 41:09 How do we avoid misallocating AI safety government grants? 51:02 Should AI safety research be done by for-profit companies?
The AI battle is heating up as Google’s Sparrow chatbot gears up to take on OpenAI’s ChatGPT. Will Sparrow be the one to reach AGI? Don’t miss out on this exciting competition! • •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••
The AI, called ProGen, works in a similar way to AIs that can generate text. ProGen learned how to generate new proteins by learning the grammar of how amino acids combine to form 280 million existing proteins. Instead of the researchers choosing a topic for the AI to write about, they could specify a group of similar proteins for it to focus on. In this case, they chose a group of proteins with antimicrobial activity.
The researchers programmed checks into the AI’s process so it wouldn’t produce amino acid “gibberish”, but they also tested a sample of the AI-proposed molecules in real cells. Of the 100 molecules they physically created, 66 participated in chemical reactions similar to those of natural proteins that destroy bacteria in egg whites and saliva. This suggested that these new proteins could also kill bacteria.
The researchers selected the five proteins with the most intense reactions and added them to a sample of Escherichia coli bacteria. Two of the proteins destroyed the bacteria.
Ever since the invention of computers in the 1940s, machines matching general human intelligence have been greatly anticipated. In other words, a machine that possesses common sense and an effective ability to learn, reason, and plan to meet complex information-processing challenges across a wide range of natural as well as abstract domains, would qualify as having a human-level machine intelligence. Currently, our machines are far inferior to humans in general intelligence. However, according to philosopher Nick Bostrom at the University of Oxford, there are several pathways that could lead to human-level intelligence in machines such as whole brain emulation, biological cognition, artificial intelligence, human-machine interfaces, as well as networks and organizations. Once this happens, it would only be a matter of time until superhuman-level machine intelligence, or simply, superintelligence is unlocked. But what exactly do we mean by ‘superintelligence’? And are there different forms of superintelligence that our A.I.s can attain in the future? Let’s take a look at what Nick Bostrom has to say in this matter!
In his book, ‘Superintelligence’ Nick Bostrom defines the term ‘superintelligence’ “to refer to intellects that greatly outperform the best current human minds across many very general cognitive domains.” So, a super-intelligent intellect, would in principle, have the capacity to completely surpass the best human minds in practically every field, including science, philosophy, arts, general wisdom, and even social skills.
It can even liquefy and move through small spaces, just like T-1000 in Terminator 2.
An international team of scientists created sea cucumber-inspired miniature robots that can quickly shift between liquid and solid states.
They built the new robots with a material they dubbed a “magnetoactive solid-liquid phase transitional machine.” The robots are also magnetic and can conduct electricity, as per a press release.
The technology can detect disorders up to six months earlier than a doctor.
Researchers are using motion capture artificial intelligence technology that brings characters to life in films like Avatar to track the onset of diseases which affect movement, according to a report by the BBC
