Artificial intelligence could be misused to design highly toxic chemical and biological weapons, warn scientists. The computer algorithms are a force for good, identifying new forms of antibiotics and medicine to combat Covid infection. But four researchers involved in AI-based drug discovery have now found that the technology could easily be manipulated to search for toxic nerve agents. The four were asked by the Swiss Federal Institute for Nuclear, Biological and Chemical Protection to look at whether AI could be used by those with ulterior motives – and their AI came up with 40,000 potentially toxic drugs in six hours. They have highlighted their concerns in the journal Nature Machine Intelligence.

The AI-powered protein-folding model AlphaFold has predicted more than 200 million proteins, nearly all such structures known to science, DeepMind said on Thursday. Proteins are complex biological molecules produced in living organisms from instructions stored in DNA. Made from as many as 20 types of amino acids, these nano-scale chains perform vital cellular tasks to carry out all sorts of bodily functions. Knowing the three-dimensional form of proteins is important since its physical structure provides hints at how it behaves, and what purpose it serves, which helps us do things like develop drugs, and create copycat proteins for those lacking them. Some proteins are helpful, such as those involved in digesting food while others can be harmful, such as those involved in the growth of tumors. Figuring out their complicated wriggly shapes, however, is difficult.

In September 2021, scientists Sean Ekins and Fabio Urbina were working on an experiment they had named the "Dr. The Swiss government's Spiez laboratory had asked them to find out what would happen if their AI drug discovery platform, MegaSyn, fell into the wrong hands. In much the way undergraduate chemistry students play with ball-and-stick model sets to learn how different chemical elements interact to form molecular compounds, Ekins and his team at Collaborations Pharmaceuticals used publicly available databases containing the molecular structures and bioactivity data of millions of molecules to teach MegaSyn how to generate new compounds with pharmaceutical potential. The plan was to use it to accelerate the drug discovery process for rare and neglected diseases. The best drugs are ones with high specificity--acting only on desired or targeted cells or neuroreceptors, for instance--and low toxicity to reduce ill effects.

An artificial intelligence model was able to create 40,000 chemical weapons compounds in just six hours, after being given the task by researchers. A team of scientists were using AI to look for compounds that could be used to cure disease, and part of this involves filtering out any that could kill a human. As part of a conference on potentially negative implications of new technology, biotech startup Collaborations Pharmaceuticals, from Raleigh, North Carolina, 'flipped a switch' in its AI algorithm, and had it find the most lethal compounds. The team wanted to see just how quickly and easily an artificial intelligence algorithm could be abused, if it were set on a negative, rather than positive task. Once in'bad mode' the AI was able to invent thousands of new chemical combinations, many of which resembled the most dangerous nerve agents in use today, according to a report by The Verge.

Marketers see great potential value in using artificial intelligence (AI) to support the use case of recommending highly targeted content to users in real time. That use case scored the highest among 49 use cases presented to marketers in the 2021 State of Marketing AI report by Drift and the Marketing Artificial Intelligence Institute. That use case scored a 3.96, putting it on the cusp of "high value" (4.0), with 5.0 being "transformative." The AI marketing use cases that trailed in the top five include: "Most websites you go to today for businesses, a human is writing the rules to say which content to recommend," Paul Roetzer, CEO and founder of the Marketing Artificial Intelligence Institute, told CMSWire in a CX Decoded Podcast. "What are the related articles? There is some basic tagging system for if they read this, then read that. Most of them are human-powered. They don't have a Netflix or a Spotify type algorithm that's actually learning preferences, knows the last 15 articles someone read, and how far along he got into them. Therein lies potential, however it's something marketers and customer experience professionals remain hopeful about: 54% of them told CMSWire researchers in the State of Digital Customer Experience 2021 report they see AI having significant impacts on digital customer experience over the next two to five years. And most of them see "gaining actionable customer insights" (27%) as the area where they see the most potential. Roetzer said it is hard to find really good solutions to do this out-of-the-box. Noz Urbina of Urbina Consulting agreed, calling the technology nascent. The bigger question for marketers beyond what kind of tools are out there is do we have the data to support the use case, according to Roetzer. And do we have a strong foundation of metadata, content tagging and content taxonomies, according to Urbina. "You need enough data, for one," Roetzer said. "Sometimes the problem is smaller data, not necessarily the cost.

Marketers see great potential value in using artificial intelligence (AI) to support the use case of recommending highly targeted content to users in real time. That use case scored the highest among 49 use cases presented to marketers in the 2021 State of Marketing AI report by Drift and the Marketing Artificial Intelligence Institute. That use case scored a 3.96, putting it on the cusp of "high value" (4.0), with 5.0 being "transformative." "Most websites you go to today for businesses, a human is writing the rules to say which content to recommend," Paul Roetzer, CEO and founder of the Marketing Artificial Intelligence Institute, told CMSWire in a CX Decoded Podcast. "What are the related articles? There is some basic tagging system for if they read this, then read that. Most of them are human-powered. They don't have a Netflix or a Spotify type algorithm that's actually learning preferences, knows the last 15 articles someone read, and how far along he got into them. Therein lies potential, however it's something marketers and customer experience professionals remain hopeful about: 54% of them told CMSWire researchers in the State of Digital Customer Experience 2021 report they see AI having significant impacts on digital customer experience over the next two to five years. And most of them see "gaining actionable customer insights" (27%) as the area where they see the most potential. Roetzer said it is hard to find really good solutions to do this out-of-the-box. Noz Urbina of Urbina Consulting agreed, calling the technology nascent. The bigger question for marketers beyond what kind of tools are out there is do we have the data to support the use case, according to Roetzer. And do we have a strong foundation of metadata, content tagging and content taxonomies, according to Urbina. "You need enough data, for one," Roetzer said. "Sometimes the problem is smaller data, not necessarily the cost.

In a prototype of the hotel of the future on display at Madrid's Fitur tourism fair, receptionists have disappeared and customers are checked-in via a mirror equipped with facial recognition. Once the client is identified, the room adapts itself automatically to all demands made at reservation: temperature, lighting, Picasso or Van Gogh in the digital frames hanging on the walls. "Technology will allow us to know what the client needs before he even knows he wants it," says Alvaro Carrillo de Albornoz, head of Spain's Hotel Technology Institute, which promotes innovation in the sector. Some hotels already offer such experiences at a more basic level. But the room prototype put on show by French technology consultancy Altran, aimed at luxury hotels, has incorporated cutting-edge speech recognition technology, allowing for instance a guest to order a pizza in 40 languages.