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Godfather of AI Geoffrey Hinton quits Google and warns over dangers of machine learning – The Guardian

Google

The neural network pioneer says dangers of chatbots were quite scary and warns they could be exploited by bad actors

The man often touted as the godfather of AI has quit Google, citing concerns over the flood of fake information, videos and photos online and the possibility for AI to upend the job market.

Dr Geoffrey Hinton, who with two of his students at the University of Toronto built a neural net in 2012, quit Google this week, the New York Times reported.

Hinton, 75, said he quit to speak freely about the dangers of AI, and in part regrets his contribution to the field. He was brought on by Google a decade ago to help develop the companys AI technology.

Hintons research led the way for current systems like ChatGPT.

He told the New York Times that until last year he believed Google had been a proper steward of the technology, but that changed once Microsoft started incorporating a chatbot into its Bing search engine, and the company began becoming concerns about the risk to its search business.

Some of the dangers of AI chatbots were quite scary, he told the BBC, warning they could become more intelligent than humans and could be exploited by bad actors.

Ive come to the conclusion that the kind of intelligence were developing is very different from the intelligence we have.

So its as if you had 10,000 people and whenever one person learned something, everybody automatically knew it. And thats how these chatbots can know so much more than any one person.

Hintons concern in the short term is something that has already become a reality people will not be able to discern what is true any more with AI-generated photos, videos and text flooding the internet.

The recent upgrades to image generators such as Midjourney mean people can now produce photo-realistic images one such image of Pope Frances in a Balenciaga puffer coat went viral in March.

Hinton was also concerned that AI will eventually replace jobs like paralegals, personal assistants and other drudge work, and potentially more in the future.

Googles chief scientist, Jeff Dean said in a statement that Google appreciated Hintons contributions to the company over the past decade.

Ive deeply enjoyed our many conversations over the years. Ill miss him, and I wish him well!

As one of the first companies to publish AI Principles, we remain committed to a responsible approach to AI. Were continually learning to understand emerging risks while also innovating boldly.

It came as IBM CEO Arvind Krishna told Bloomberg that up to 30% of the companys back-office roles could be replaced by AI and automation within five years.

Krishna said hiring in areas such as human resources will be slowed or suspended, and could result in around 7,800 roles being replaced. IBM has a total global workforce of 260,000.

The Guardian has sought comment from IBM.

Last month, the Guardian was able to bypass a voice authentication system used by Services Australia using an online AI voice synthesiser, throwing into question the viability of voice biometrics for authentication.

Toby Walsh, the chief scientist at the University of New South Wales AI Institute, said people should be questioning any online media they see now.

When it comes to any digital data you see audio or video you have to entertain the idea that someone has spoofed it.

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Godfather of AI Geoffrey Hinton quits Google and warns over dangers of machine learning - The Guardian

After Quitting Google, ‘Godfather of AI’ Is Now Warning of Its Dangers – Gizmodo

Megalithic tech companies such as Google, Meta, and Microsoft are so obsessed with AI development it seems impossible to steer any of them toward slowing down and actually thinking about the repercussions. Now one of the most prominent faces in artificially intelligence research, former Googler Dr. Geoffrey Hinton, has come down hard on the full-spring pace of AI development, ultimately calling for some kind of global regulation.

Googles Antitrust Case Is the Best Thing That Ever Happened to AI

According to an interview with The New York Times, Hinton, an award-winning researcher on AI, neural networks, and machine learning, is no longer so comfortable pushing the boundaries of AI development without many kind of regulation or stopgap. The 75-year-old Hinton, who was a lead researcher in any aspects of AI development at Google, has come out saying It is hard to see how you can prevent the bad actors from using [AI] for bad things.

He directly compared himself to Robert Oppenheimer, who helped develop the atomic bomb for the U.S. While Oppenheimer had made statements about pursuing science for sciences sake, Hinton instead said I dont think they should scale [AI] up more until they have understood whether they can control it. He further shared his concerns that AI would lead to massive job disruptions around the world.

Hinton got his Godfather title not with any offer you cant refuse, but from decades of research on AI. This came to a head with the neural network he helped build in 2012 with two of his students at the University of Toronto. That network was a machine learning program that could teach itself to identify objects like dogs, flowers, and so on, and it became a major stepping stone for modern transformer-based AI like diffusion AI image generators and large language models.

Google had originally acquired the company formed out of Hintons Toronto-based research in 2013. This let him establish a Toronto-based element of the Google Brain team overseeing AI development. After that, Google went on an AI spending spree when it acquired deep learning company DeepMind in 2014. Hintons company, according to a 2021 Wired report, received numerous offers from tech giants including Microsoft and China-based Baidu, both of which are deep in the muck with their own push into AI development. In a March interview with CBS News, Hinton compared the recent rapid advancements in AI to the Industrial revolution or electricityor maybe the wheel.

Its unclear when Hinton made this heel-turn, but just a few months ago he was instead referring to AI as a supernaturally precocious child. He compared AI training to caterpillars feeding on nutrients to become butterflies, further calling OpenAIs GPT-4 large language model humanitys butterfly.

According to the Times, in April Hinton told Google he planned to leave, and finally cut the cord after a call with CEO Sundar Pichai last Thursday. Though The New York Times implied that Hinton had left Google in order to specifically take umbrage with his old boss, the Turing Award winner claimed he only wished to speak up on the dangers of AI, adding Google has acted very responsibly.

Hintons departure comes at a time of massive reorganization at his former company after massive layoffs. Last month, Google announced it was consolidating two of its most major AI teams together. Combining the Google Brain and DeepMind teams into one unit and also reorganized its AI leadership, with Brain lead Jeff Dean being moved to a chief scientist position while DeepMind CEO Demis Hassabis is set to take control of all AI development.

So far, the overt calls for stalling AI development have come from outside big tech. In March, hundreds of leading minds and researchers circulated an open letter demanding companies pause advanced AI systems. The letter criticized how major tech companies were locked in an out-of-control race to develop and deploy ever more powerful digital minds that nobody could predict or control. Though thats not to say folks inside these companies dont have qualms. A recent report from Bloomberg claimed that people inside Google were especially concerned with the companys Bard AI. Staff said the chatbot was so bad it was constantly providing misinformation and lies to users.

Want to know more about AI, chatbots, and the future of machine learning? Check out our full coverage of artificial intelligence, or browse our guides to The Best Free AI Art Generators, The Best ChatGPT Alternatives, and Everything We Know About OpenAIs ChatGPT.

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After Quitting Google, 'Godfather of AI' Is Now Warning of Its Dangers - Gizmodo

Machine learning and statistical classification of birdsong link vocal acoustic features with phylogeny | Scientific Reports – Nature.com

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Machine learning and statistical classification of birdsong link vocal acoustic features with phylogeny | Scientific Reports - Nature.com

10 Best Ways to Earn Money Through Machine Learning in 2023 – Analytics Insight

10 best ways to earn money through machine learning in 2023 are enlisted in this article

10 best ways to earn money through machine learning in 2023 take advantage of the early lifespan and its adoption may then leverage this into other apps.

Land Gigs with FlexJobs: FlexJobs is one of the top freelance websites for finding high-quality employment from actual businesses. Whether you are a machine learning novice or a specialist, you may begin communicating with clients to monetize your skills by working on freelancing projects.

Become a Freelancer or List your Company to Hire a Team on Toptal: Toptal is similar to FlexJobs in that it is reserved for top freelancers and top firms wanting to recruit freelance machine learning programmers. This is evident in the hourly pricing given on the site as well as the caliber of the programmers.

Develop a Simple AI App: Creating an app is another excellent approach to generating money using machine learning. You may design a subscription app in which users can pay to access certain premium features. Subscription applications are expected to earn at least 50% more money than other apps with various sorts of in-app sales.

Become an ML Educational Content Creator: You can make money with machine learning online right now if you start teaching people about machine learning and its benefits. To publish and sell your course, use online platforms that provide teaching platforms, such as Udemy and Coursera.

Create and Publish an Online ML Book: You may create a book to provide extraordinary insights on the power of 3D printing, robots, AI, synthetic biology, networks, and sensors. Online book publication is now feasible because of systems such as Kindle Direct Publication, which provides a free publishing service.

Sell Artificial Intelligence Devices: Another profitable enterprise to consider is selling GPS gadgets to automobile owners. GPS navigation services can aid with traffic forecasting. As a result, it can assist car users in saving money if they choose a different route to work. Based on everyday experiences, you may estimate the places likely to be congested with access to the current traffic condition.

Generate Vast Artificial Intelligence Data for Cash: Because machine learning can aid in the generation of massive amounts of data, you can benefit from providing AI solutions to various businesses. AI systems function similarly to humans and have a wide range of auditory and visual experiences. An AI system may learn new things and be motivated by dynamic data and movies.

Create a Product or a Service: AI chatbots are goldmines and a great method to generate money with machine learning. Creating chatbot frameworks for mobile phones in the back endand machine learning engines in the front end is an excellent way to make money quickly. Making services like sentiment analysis or Google Vision where the firm or user may pay after making numerous queries per month is another excellent approach to gaining money using ML.

Participate in ML Challenges: You may earn money using machine learning by participating in and winning ML contests, in addition to teaching it. If you are a guru or have amassed a wealth of knowledge on this subject, you may compete against other real-world machine-learning specialists in tournaments.

Create and License a Machine Learning Tech: If you can develop an AI technology and license it, you can generate money by selling your rights to someone else. As the licensor, you must sign a contract allowing another party, the licensee, to use, re-use, alter, or re-sell it for cash, compensation, or consideration.

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10 Best Ways to Earn Money Through Machine Learning in 2023 - Analytics Insight

22% churn in Indian job market likely by next 5 years; AI, tech among top roles – Hindustan Times

A 22% churn in the Indian job market is estimated in the next five years where artificial intelligence, machine learning and data segments are likely to emerge as top job producing areas, according to a study by the World Economic Forum.

The study, Future of Jobs report, said around 61% of Indian companies think broader application of environment, social and governance (ESG) standards will drive job growth. Similarly, 59% of companies think adopting new technologies will develop employment, whereas 55% think broadening digital access could bring in more jobs.

India and China were found to be more positive than the global average when it comes to comparing with countries' viewpoints on talent availability while hiring. However, India has been placed among seven countries where growth in social jobs was found to be slower than non-social jobs.

Globally, the report discovered there is a 23% job market churn with 69 million new jobs expected to be created and 83 million are predicted to be eliminated by 2027.

"Almost a quarter of jobs (23 per cent) are expected to change in the next five years through growth of 10.2 per cent and decline of 12.3 per cent (globally)," the WEF said.

The survey was conducted in 803 companies across 45 economies around the world that collectively employ over 11.3 million workers.

It noted that technology has posed both opportunities and challenges to labour market where both the fastest-growing as well as declining roles are driven by it and the digitalisation.

The report further pointed out that only half of the employees have access to adequate training opportunities and by 2027, six out of 10 workers will require proper training.

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22% churn in Indian job market likely by next 5 years; AI, tech among top roles - Hindustan Times