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OpenAI released an analysis showing that since 2012, the amount of compute used in the largest AI training runs has been increasing exponentially with a 3.5 month-doubling time (by comparison, Moore’s Law had an 18-month doubling period).
Since 2012, this metric has grown by more than 300,000x (an 18-month doubling period would yield only a 12x increase). Improvements in compute have been a key component of AI progress, so as long as this trend continues, it’s worth preparing for the implications of systems far outside today’s capabilities.
The government is banking on a multi-stakeholder taskforce, which was set up in February, to formulate a concrete strategy and framework for “employment of AI for national security and defence needs” in the years ahead.
“The world is moving towards AI-driven warfare. India is also taking necessary steps to prepare our armed forces because AI has the potential to have a transformative impact on national security. The government has set up the AI taskforce to prepare the roadmap for it,” said Union defence production secretary Ajay Kumar, speaking exclusively to TOI.
Professor Rose Luckin asks: Will the classroom of the future have a machine teaching children their times tables, instructing them in foreign languages? She says that alongside how to read, write and count, our children should be taught the basics of AI. Not just the technical detail of how to code but the principles and logic on which the systems are designed.
We need to develop in students the ability to ask good questions, to challenge the evidence we present to them. One then hopes these children will be less likely than previous generations to complete a Facebook quiz that involves handing over their personal data to shadowy market research firms.
Amazon’s Alexa will soon be making its way into more people’s homes via Acer notebooks, which are shipping with the voice-activated assistant pre-installed, Acer announced.
Acer said the Spin 3 and Spin 5 lines, which are available now, come with Alexa. Eventually, Acer plans to roll out Alexa across its entire PC portfolio. In the coming weeks, the Acer Nitro 5 Spin convertible gaming notebook line will come with Alexa, as will select Aspire, Switch and Swift notebooks.
Yesterday, Emergence Capital announced it has raised a $435 million fund to invest in companies that use machine learning to help people increase productivity at work.
The fund will focus especially on companies that provide coaching powered by data and conversational AI to help people perform their jobs better. Emergence has previously made a number of similar investments, including in call center analysis company Chorus.ai; recruiter chatbot Mya; and Textio, which is using conversational AI to make better recruitment messages for companies that are hiring.
Alibaba is teaming up with SenseTime, the world’s highest-valued AI startup, to launch a not-for-profit artificial intelligence lab in Hong Kong in a
bid to make the city a global hub for artificial intelligence.
One of the country’s biggest hospitals has unveiled sweeping plans to use artificial intelligence to carry out tasks traditionally performed by doctors and nurses, from diagnosing cancer on CT scans to deciding which A&E patients are seen first.
The three-year partnership between University College London Hospitals (UCLH) and the Alan Turing Institute aims to bring the benefits of the machine learning revolution to the NHS on an unprecedented scale. The first project will focus on improving the hospital’s accident and emergency department, which like many hospitals is failing to meet government waiting time targets.
Chinese internet companies and government departments employ several million full-time censors to police content the ruling Communist party finds objectionable and most internationally dominant internet services, such as Google, Facebook and Twitter, are entirely blocked in China.
As China’s online population has boomed, human censors have been overwhelmed with an ever-growing wave of online content. So companies like iQiyi, a top video-streaming platform, are turning to machine learning to filter content Beijing wants to ban. By deploying machine learning, the company’s team of content censors only doubled over that time to roughly 500 people. Their job is to remove pornographic and violent content, as well as themes deemed “politically sensitive” by the authoritarian government, such as homosexuality.