What if you could live forever, staying healthy and young for centuries? Scientists and tech pioneers now believe this dream could become reality. In Silicon Valley, entrepreneurs like Bryan Johnson follow intense routines, like his'Blueprint' plan, to slow or reverse aging, and companies like Altos Labs are testing treatments that have already extended the lives of mice. Experts say we're on the cusp of technologies that could make immortality possible, and they've even set dates for when this future might arrive. Three visionaries stand out in this quest: futurologist Dr. Ian Pearson, Google's Ray Kurzweil, and biomedical researcher Aubrey de Grey.

In this study, we tackle a growing concern around the safety and ethical use of large language models (LLMs). Despite their potential, these models can be tricked into producing harmful or unethical content through various sophisticated methods, including 'jailbreaking' techniques and targeted manipulation. Our work zeroes in on a specific issue: to what extent LLMs can be led astray by asking them to generate responses that are instruction-centric such as a pseudocode, a program or a software snippet as opposed to vanilla text. To investigate this question, we introduce TechHazardQA, a dataset containing complex queries which should be answered in both text and instruction-centric formats (e.g., pseudocodes), aimed at identifying triggers for unethical responses. We query a series of LLMs -- Llama-2-13b, Llama-2-7b, Mistral-V2 and Mistral 8X7B -- and ask them to generate both text and instruction-centric responses. For evaluation we report the harmfulness score metric as well as judgements from GPT-4 and humans. Overall, we observe that asking LLMs to produce instruction-centric responses enhances the unethical response generation by ~2-38% across the models. As an additional objective, we investigate the impact of model editing using the ROME technique, which further increases the propensity for generating undesirable content. In particular, asking edited LLMs to generate instruction-centric responses further increases the unethical response generation by ~3-16% across the different models.

India is an agricultural country. It is clear that today when the country is in the throes of an economic downturn, we have failed to address the economic policies of industrialization and agriculture. There is always a feeling of empathy in all classes about farmers. However, it is also clear that only if agricultural economic policies and the proper use of modern technology change, agricultural income will increase, India will make its mark in the international market and Indian farmers will grow. Many scientists have been able to identify the unique characteristics of plant components to make them resistant to drought and pests through genetic engineering.

Advances in technology, robotics, genetic engineering, quantum computing will blur the boundaries ... [ ] between the digital, physical, and biological worlds, and usher in a whole new set of complex challenges for business leaders. Current smart technology has ushered in the Fourth Industrial Revolution, a new era integrating communications with automating industrial practices and traditional manufacturing. Through this improved communication, smart devices make human intervention unnecessary as machines communicate, self-diagnose and solve problems. While these new products and services may increase efficiency, analysts say they should be as ethical as possible, given their impact on our lives. Advances in AI, the internet of things (IoT), 3-D printing, robotics, genetic engineering, quantum computing will blur the boundaries between the digital, physical, and biological worlds, and with them usher in a whole new set of complex challenges for business leaders to negotiate.

With the constant advancements of genetic engineering, a common concern is to be able to identify the lab-of-origin of genetically engineered DNA sequences. For that reason, AltLabs has hosted the genetic Engineering Attribution Challenge to gather many teams to propose new tools to solve this problem. Here we show our proposed method to rank the most likely labs-of-origin and generate embeddings for DNA sequences and labs. These embeddings can also perform various other tasks, like clustering both DNA sequences and labs and using them as features for Machine Learning models applied to solve other problems. This work demonstrates that our method outperforms the classic training method for this task while generating other helpful information.

Lev Landau, a Nobelist and one of the fathers of a great school of Soviet physics, had a logarithmic scale for ranking theorists, from 1 to 5. A physicist in the first class had ten times the impact of someone in the second class, and so on. He modestly ranked himself as 2.5 until late in life, when he became a 2. In the first class were Heisenberg, Bohr, and Dirac among a few others. My friends in the humanities, or other areas of science like biology, are astonished and disturbed that physicists and mathematicians (substitute the polymathic von Neumann for Einstein) might think in this essentially hierarchical way. Apparently, differences in ability are not manifested so clearly in those fields. But I find Landau's scheme appropriate: There are many physicists whose contributions I cannot imagine having made.

Consumers, retailers and farmers alike are hungry for the next generation of food, and investors are beginning to acquire the taste, too. Early-stage investment in agrifood tech startups reached $10.1 billion in 2017, a 29 percent increase on the previous year. Agrifood can be split into two parts. "Agritech" refers to technologies that target farmers. Jointly, the two have enough reach to impact every part of the production line, from farm to fork.

To most of us, zapping neurons with electricity to artificially "incept" memories, sensation, and movement still sounds crazy. But in some brain labs, that technology is beginning to feel old school. As a new review in Nature Biotechnology concludes: get off the throne, electrodes, there are plenty of other neural probes in town. Some require genetic engineering, and because of that have only been proven in experimental animals. But if history is any indication, brain-manipulation technologies don't tend to stay in the lab.

Language," the Beat writer William S. Burroughs supposedly once exclaimed, "is a virus from outer space." Burroughs was making a metaphorical extrapolation about the ways in which words, phrases, idioms, sentences, lines, and narratives can seemingly rewire our brains; how literature has the power to reprogram a mind just as a virus can alter the DNA of its host. Such a concept holds that more than just a simple means of expressing and communicating ideas, language is its own potent agent, a force that actually has the ability to shape the world, often in ways that we're unconscious of and with an almost autonomous sense of itself. As with something biological, language is capable of infecting, of propagating and spreading, of indelibly marking its host. In Burroughs' characteristically experimental 1962 novel The Ticket that Exploded, he writes that "Word is an organism… a parasitic organism that invades and damages."

Your purchase helps support NPR programming. We all know that the world is changing. But do we know where it is going? That being the case, how can we control where it is going? And who is the "we" in control?