As all readers of this essay know, I am not in any way expert in machine learning (ML) and large language models (LLMs), so my descriptions and observations are, at best, lightweight cartoons of what is actually going on. Please keep this in mind as you read this. Some of you may remember Spock's death in Star Trek II (Wrath of Khan) and the brief scene where Spock mind-melds with Dr. McCoy: Spock says "remember" while depositing his katra in McCoy's brain in anticipation of self-sacrifice to save the starship Enterprise. As I read about yet another new breakthrough in artificial intelligence (AI) from Google Research, I thought of that scene. The new idea, christened "TITAN", is for a ML system to continue learning while in use after training.a

I met the most rational person I know during my freshman year of college. Greg (not his real name) had a tech-support job in the same computer lab where I worked, and we became friends. I planned to be a creative-writing major; Greg told me that he was deciding between physics and economics. He'd choose physics if he was smart enough, and economics if he wasn't--he thought he'd know within a few months, based on his grades. We roomed together, and often had differences of opinion.

In the last two decades, since the first exoplanet has been discovered, scientists have identified more than 4000 planets orbiting other stars, of which half are in multi-planet systems. Out of these, at least 700 of them have planets which can be at potential risk of devastating collision. Researchers even believe that there are possibilities of many collisions that have already taken place that we are not aware of. Several questions, such as how planets organise themselves, prevent themselves from colliding into each other or how they remain stable have been the centre of research for many years. One of the requirements to be able to detect these are to make sure that a planetary system is stable.

While it was a sci-fi concept, then, it is no longer a fiction anymore. Scientists around the world are using AI algorithms to predict the life of other planets in the solar system, detecting the presence of water, finding out the possibility of a Blackhole, or determining the orbital curve of a celestial object. According to NASA officials, AI could also aid in the search for life on alien planets and the detection of nearby asteroids in space. What took years for earlier astronomers to discover can now be done in a shorter time duration by using machine learning models of AI. Now researchers from Princeton University have claimed to have found a way to predict if a planet will clash with another in its path.

A team of NASA astrophysicists has put the fate of entire star systems in the hands of an AI algorithm. The system -- dubbed SPOCK -- by NASA and Princeton University astrophysicist Daniel Tamayo, doesn't actually decide which worlds will live and die. But it can predict the paths of exoplanets, and determine which ones will remain stable and which will crash into other worlds or stars, far more accurately and at greater scale than humans ever could. Since the first exoplanet was discovered in 1995, scientists have identified more than 4,000 worlds elsewhere. Over 700 of them are in star systems containing more than one planet, Tamayo said in a press release, which potentially puts them at risk of devastation collisions.

While three planets have been detected in the Kepler-431 system, little is known about the shapes of their orbits. On the left are a large number of superimposed orbits for each planet that are consistent with observations. An international team of astrophysicists led by Princeton's Daniel Tamayo removed all the unstable configurations that would have already collided and couldn't be observed today. Doing this with previous methods would take over a year of computer time. With their new model SPOCK, it takes 14 minutes.

How do planetary systems--like our solar system or multi-planet systems around other stars--organize themselves? Of all of the possible ways planets could orbit, how many configurations will remain stable over the billions of years of a star's life cycle? Rejecting the large range of unstable possibilities--all the configurations that would lead to collisions--would leave behind a sharper view of planetary systems around other stars, but it's not as easy as it sounds. "Separating the stable from the unstable configurations turns out to be a fascinating and brutally hard problem," said Daniel Tamayo, a NASA Hubble Fellowship Program Sagan Fellow in astrophysical sciences at Princeton. To make sure a planetary system is stable, astronomers need to calculate the motions of multiple interacting planets over billions of years and check each possible configuration for stability--a computationally prohibitive undertaking.

Occasional creepiness notwithstanding, kids seem to love Alexa. Jeremy Cornforth works at the State Department in Washington and is the father of 5-year-old twins. When he brought home an Echo, "We just told them it was a speaker, and it was a computer, and it could understand the things they said. They took to it immediately," he said. "There's a little power struggle now over who gets to control it."

Cisco introduces Spark Assistant and Spark Room 70, and lays out its AI roadmap. Cisco this week is holding its annual reseller conference, Partner Summit, in Dallas. When Rowan Trollope, SVP & GM of IoT and Applications at Cisco, delivered his keynote today, the company unveiled its AI-powered voice assistant with the not so inventive name of "Cisco Spark Assistant." There is, of course, a veritable cornucopia of voice assistants out there, as we can ask Siri, Google, Alexa, Cortana or other popular AIs a question and get a prompt answer back. The reasons that communications and collaboration industry professionals should care is because the Spark AI is entirely focused on improving meetings.

Good parties diverge widely; all bad parties are bad in the same way. I am trapped at a dull dinner following a dull talk: part of a series of dinners and talks that grad students organise, unpaid (though at considerable expense to themselves--experience! exposure!), to provide free content for the dull grad program I will soon leave. The Thai food is good. The man sitting across from me and a little down the way, a bellicose bore of vague continental origin, is execrable. He is somehow attached to a mild woman who is actually supposed to be here: a shy, seemingly blameless new grad student who perpetually smiles apologetically on his behalf, in an attempt to excuse whatever he's just said. One immediately understands that she spends half her life with that worry in her eyes, that Joker-set to her mouth, and that general air of begging your pardon for offences she hadn't even had the pleasure of committing. There is always such a woman at bad parties. She has always either found ...