Tag: machine learning

Google’s search for an AI future as it turns 25

The tech giant Google and I almost share the same birthday… give or take a few years.

Google turns 25 this month (I’ll have a few more candles on my cake) – and finds itself in a tech landscape that has changed dramatically since founders Larry Page and Sergey Brin started it in 1998.

Back then Google was only a search engine, and it lived for its first few months in the garage of Susan Wojcicki – the future boss of YouTube.

You do not need me to tell you how well that search engine worked out. It has been 17 years since the word Google officially entered the dictionary. I remember a BBC discussion about whether we should use it as a verb on-air because of its potential to be a free advert for the firm.

That company – now part of a larger parent group called Alphabet – has since diversified into pretty much every area of tech and dominates some of them to an extent which sometimes troubles anti-competition regulators. Right now it is trying to Google itself into pole position in the AI race – but some say it has already fallen behind.

Hits and misses
Email and smartphones, software and hardware, driverless cars, digital assistants, YouTube – Google has spawned (and acquired) hundreds of products and services. Not all of them have worked out.

There are 288 retired projects listed on the Killed by Google website, include gaming platform Stadia and budget VR headset Google Cardboard.

Google vice-president Phil Harrison showed off the Stadia controller on-stage at its launch in 2019

The question now is whether Google can maintain its omnipresence in the rapidly evolving world of artificial intelligence.

There have been mutterings, including from within, that it has fallen behind. A leaked memo from a Google engineer found its way on to the net, in which he said the firm had no AI “secret sauce” and was not in a position to win the race.

This feeling was further fuelled by the battle of the bots.

What is AI, is it dangerous and what jobs are at risk?
‘Google killer’ ChatGPT sparks AI chatbot race
Google what our chatbot tells you… says Google
For many people, the first time they knowingly interacted with AI – and were impressed by it – came in the form of ChatGPT, the viral AI chatbot which exploded into the world in November 2022.

Its creator OpenAI has received billions of dollars in investment from Microsoft, which is now working it into its own products, including the Bing search engine and Office 365.

ChatGPT has been dubbed the “Google killer” because of the way it can answer a question in one go, rather than serve up pages and pages of search results.

It uses a language-processing architecture called a transformer which was actually invented by Google, but when Google followed up a few months later with its own rival Bard, it had nowhere near the same impact.

Bard was given a surprisingly cautious launch. It was not for under-18s, the tech giant said, and it was described to me as “an experiment” by a senior exec.

Perhaps part of its caution was in part a result of a weird situation which preceded Bard.

Source: https://www.bbc.com/news/technology-66659361

Simon Cowell replaced by a robot? Scientists use AI to pick hit songs

Robot hand presses the key on the piano, the machine learning technology. (Credit: Shutterstock)

CLAREMONT, Calif. — A robot could be coming for the job of prominent music producers and talent show judges like Simon Cowell, according to new research. Scientists have utilized artificial intelligence to identify hit pop songs with an impressive 97 percent accuracy. Such a computer system could render TV talent show judges redundant, replicating their skills at a significantly reduced cost.

The AI, which utilizes a neural network, can also enhance the efficiency of streaming services. According to researchers in California, the system is so straightforward that it can be applied to films and TV shows.

“By applying machine learning to neurophysiologic data, we could almost perfectly identify hit songs,” says Paul Zak, a professor at Claremont Graduate University and senior author, in a media release. “That the neural activity of 33 people can predict if millions of others listened to new songs is quite amazing. Nothing close to this accuracy has ever been shown before.”

With tens of thousands of songs released daily, it becomes challenging for apps like Spotify, Tidal, and Deezer to select which ones to add to playlists. Previous attempts to identify songs that will resonate with a large audience have had only a 50-percent success rate. However, Prof. Zak and his colleagues believe that their method is almost twice as effective.

During the study, participants wore skull-cap brain scanners while listening to a set of 24 songs. They were also asked about their preferences and provided basic demographic data. The experiment measured neurophysiological responses.

“The brain signals we’ve collected reflect activity of a brain network associated with mood and energy levels,” Zak says.

(© MMPhoto21 – stock.adobe.com)

This enabled the team to predict market outcomes, including the number of streams a song might receive, based on responses from a few volunteers.

The team’s approach, called “neuroforecasting,” uses brain cell activity from a small group of people to predict population-level effects. A statistical model identified potential chart hits 69 percent of the time, but this jumped to 97 percent when machine learning was applied to the data. The team found that even by analyzing neural responses to only the first minute of songs, they achieved a success rate of 82 percent.

Source : https://studyfinds.org/simon-cowell-ai-pick-hit-songs

Exit mobile version