Tag: artificial general intelligence

Google’s discontinued 90’s AI project Big Brain Brad revived as ChatGPT alternative

Seeking to capitalize on the success of ChatGPT, Google is attempting to develop a lower cost AI alternative capable of serving more low-tech and outdated industries.  The once abandoned 90’s AI project Big Brain Brad has proven up to the challenge in a number of areas that in a former era were exclusively the domain of highly specialized human agents.    

In numerous trials, Big Brain Brad has demonstrated the ability to man hundreds of psychic hotline phone banks, while delivering accurate predictions at or above industry standards.  What’s more, while human psychics are often limited to only one form of psychic forecasting, like astrology or tarot cards, Big Brain Brad employs dozens of disciplines to formulate the most current and accurate psychic readings.  “B-Cubed looks at star charts, tea leaves, birthdays, gravitational waves, tarot, biofeedback, you name it.  Hell, we’re even close to a breakthrough that allows Brad to do palm readings,” said Google assistant director of senior AI applications Yuri Testikov.   

Another area of promise for Big Brain Brad is the music industry.  Jam bands from Dave Matthews to Phish to Blues Traveller have all signed on to Big Brain Brad’s management and public relations services.  “Brad does it all: venues, hotels, transportation, website, publicity, and the best part is the dude never sleeps.  He’s working for us 24/7.  It’s like having a manager who’s always coked to the gills, but never crashes, costs a lot less and isn’t as horny,”  said one jam band pioneer who wished to remain anonymous.

“Big Brain Brad’s 90’s origins seem to make him especially suited to certain types of industries that wish to remain competitive in the coming decades,” Testikov said.  “However, we’re also working on developing B-Cubed’s social networking capabilities.  Soon we’ll be rolling out a version of Big Brain Brad that’s a drum circle facilitator.  Whether you’re looking to do a zoom circle or just connect with other bongo players in the park, Big Brain Brad can hook you up.”

DeepMind scientists: “Creating artificial general intelligence is really fucking hard, maybe we should just dumb down our world.”

Scientists for DeepMind, the AI project owned by Google parent company Alphabet, seem to have run into some roadblocks recently regarding its projects development.  According to a piece written by Gary Marcus for Wired, “DeepMind’s Losses and the Future of Artificial Intelligence,” DeepMind lost $572 million last year for its deep pocketed parent company and has accrued over a billion dollars in debt.  While those kinds of figures are enough to make the average parent feel much better about their child’s education dollars, the folks at Alphabet are starting to wonder if researchers are taking the right approach to DeepMind’s education.

So what’s the problem with DeepMind?  Well, for one thing, news of DeepMind’s jaw-dropping video game achievements have been greatly exaggerated.  For instance, in StarCraft it can kick ass when trained to play on a single map with a single character. But according to Marcus, “To switch characters, you need to retrain the system from scratch.”  That doesn’t sound promising when you’re trying to develop artificial general intelligence. Also, to learn it needs to acquire huge amounts of data, requiring it to play a game millions of times before mastery, far in excess of what a human would require.  Additionally, according to Marcus, the energy it required to learn to play Go was similar “to the energy consumed by 12,760 human brains running continuously for three days without sleep.” That’s a lot of human brains, presumably fueled by pizza and methamphetamine if they’re powered on for three days without sleep. 

A lot of DeepMind’s difficulties stem from the way it learns.  Deep reinforcement learning involves recognizing patterns and being rewarded for success.  It works well for learning how to play specific video games. Throw a little wrinkle at it, however, and performance breaks down.  Marcus writes: “In some ways, deep reinforcement learning is a kind of turbocharged memorization; systems that use it are capable of awesome feats, but they have only a shallow understanding of what they are doing. As a consequence, current systems lack flexibility, and thus are unable to compensate if the world changes, sometimes even in tiny ways.”

All of this has led researchers to question whether deep reinforcement learning is the correct approach to developing AI general intelligence.  “We are discovering that the world is a really fucking complex place,” says Yuri Testicov, DeepMind’s Assistant Director of Senior Applications.  “I mean, it’s one thing to sit in a lab and become really great at a handful of video games, it’s totally another to try to diagnose medical problems or discover clean energy solutions.” 

Testicov and his fellow researchers are discovering that the solution to DeepMind’s woes may not come from a new approach to learning, but instead, the public may need to lower the bar on expectations.  “We’re calling on the people of earth to simplify and dumb down,” adds Testicov. “Instead of expecting DeepMind to come along and grab the world by the tail, maybe we just need to make the world a little easier for it to understand.  I mean, you try going to the supermarket and buying a bag of tortilla chips. Not the restaurant kind but the round ones. Not the regular but the lime. Make sure they’re low sodium and don’t get the blue corn. That requires a lot of complex awareness and decision making.  So, instead of expecting perfection, if we send a robot to the supermarket and it comes back with something we can eat, we say we’re cool with that.”  

Testicov has some additional advice for managers thinking about incorporating AI into the workplace.  “If you’re an employer and you’re looking to bring AI on board, don’t be afraid to make accommodations for it, try not to be overly critical of job performance, and make sure you reward good work through positive feedback and praise,” says Testicov.  “Oh sorry, that’s our protocol for managing millennials. Never mind.”