Today we discuss Elon Musk’s recent remarks at the World Government Summit in Dubai about a future in which humans must, to use his word, “merge” with robots in order to have a competitive advantage.
Do you agree with Musk and think that we should be merging humans and robots to create what he referred to as “cyborgs”? Voice your opinion by clicking ‘Yes’ or ‘No’ below and please include a comment as well.
Humans must become cyborgs if they are to stay relevant in a future dominated by AI. That was the warning from Tesla founder Elon Musk, speaking at an event in Dubai this weekend.
Musk argued that as AI becomes more sophisticated, it will lead to mass unemployment. “There will be fewer and fewer jobs that a robot can’t do better,” he said at the World Government Summit.
If humans want to continue to add value to the economy, they must augment their capabilities through a “merger of biological intelligence and machine intelligence”. If we fail to do this, we’ll risk becoming “house cats” to AI.
Yesterday the general artificial intelligence R&D company GoodAI launched its General AI Challenge to tackle crucial research problems in human-level AI development. GoodAI will distribute $5mil in prizes among the various rounds of the multi-year Challenge.The Challenge kicks off with a 6-month “warm-up” round, open to the worldwide community of researchers and programmers (both for individuals and teams).
Following a high-profile and very heated court hearing over ownership of the patents for gene-editing technology CRISPR-Cas9, judges at the United States Patent and Trademark Office in Alexandria, Virginia, ruled today that the technology belongs to the Broad Institute of MIT and Harvard, not the University of California Berkeley, STAT News first reported.
This is a big blow to UC Berkeley, as this technology is worth potentially billions or even trillions of dollars, TechCrunch’s Sarah Buhr previously noted. That’s because CRISPR-Cas9 is perhaps the most important breakthrough in biotech of our time.
In a one-sentence ruling, the judges said, “In light of the determination that the parties’ claims do not interfere, we enter judgment of no interference-in-fact, which neither cancels nor finally refuses either parties’ claims.”
A combination of elements including massive distributed computing power, the decreasing cost of data storage, and the rise of open source frameworks is helping to accelerate the application of AI. Research conducted by Accenture indicates that, by 2035, AI could double economic growth rates in 20 countries, and boost labor productivity by up to 40 percent. The increasing importance of AI has significant implications for financial institutions and particularly for those institutions’ own finance function. In short, AI has the potential to fundamentally transform banks’ finance function within the next decade – if not sooner.
AI can help banks dramatically improve operational efficiency and gain a much clearer understanding of where they are going, but it is still up to humans to make the big strategic decisions and set the course for AI and related technologies to help deliver profitable growth.
An incisive understanding of user personality is not only essential to many scientific disciplines, but also has a profound business impact on practical applications such as digital marketing, personalized recommendation, mental diagnosis, and human resources management. Previous studies have demonstrated that language usage in social media is effective in personality prediction.
However, except for single language features, a less researched direction is how to leverage the heterogeneous information on social media to have a better understanding of user personality. In this paper, Honghao Wei et. al. propose a Heterogeneous Information Ensemble frame work, called HIE, to predict users’ personality traits by integrating heterogeneous information including self-language usage, avatar, emoticon, and responsive patterns.
Advances in technology—improved machine-learning algorithms and supercomputers as well as the ability to store and work with vastly greater amounts of data—may now give Paul Johnson, a geophysicist at Los Alamos National, and his team a new edge in using AI to predict earthquakes. “If we had tried this 10 years ago, we would not have been able to do it,” says Johnson, who is collaborating with researchers from several institutions.
Along with more sophisticated computing, he and his team are trying something in the lab no one else has done before: They are feeding machines raw data—massive sets of measurements taken continuously before, during and after lab-simulated earthquake events. They then allow the algorithm to sift through the data to look for patterns that reliably signal when an artificial quake will happen. In addition to lab simulations, the team has also begun doing the same type of machine learning analysis using raw seismic data from real temblors.
Baidu Inc.’s spate of acquisitions is starting to show a trend. AI and VR are the search giant’s favourite dishes these days, and the Chinese startup Raven Tech
is the latest item from the menu.
Just two days after Baidu Ventures said it joined a Series B investment in 8i, a US VR startup, Baidu Inc. announced the purchase of Beijing-based Raven. The cost wasn’t disclosed, but Tim Culpan from Bloomberg guesses it was about $100 million.
Raven Tech has been plugging away at voice input and NLP, and integrating those technologies into practical applications. For example, you can use it to voice chat with friends about dinner plans, and Raven Tech will connect with smartphone apps to help you scout for restaurants and advise on transportation options.
Peer-to-peer selling sites – like Craigslist, Trademe, Gumtree, and eBay – are hugely popular, largely thanks to the fact that you can get some serious bargains through them. But they’re not without their risks. When you buy something through these sites, there’s always a chance that you might not get what you pay for. Or worse, that you’ll sell an item, and not receive the money.
To address this problem, Spanish startup Traity and Australian insurer Suncorp have devised a chat bot-driven approach to insuring peer-to-peer transactions.
The product, called Kevinsured, is pretty straightforward. When you buy or sell something, you message Kevin and inform him of the nature and size of the transaction. Kevin validates the identities of both parties, and once the transaction is approved, it will create a guarantee which is recorded against the blockchain. This protects both buyer and seller against fraud.