Lifeboat Foundation

Panasonic has begun testing robotic mobility devices at the newly constructed Takanawa Gateway train station in Tokyo.

The effort is art of a plan to bring a series of automated services to the airport and surrounding facilities that are part of a massive redevelopment project in the surrounding Shinagawa business district.

Three mobility devices, essentially intelligent electric wheelchairs, will be used as a single group in the trial. The experiment will focus on ensuring the safety of passengers with mobility issues as they are transported throughout the huge facilities.

Google today announced that it has signed up Verizon as the newest customer of its Google Cloud Contact Center AI service, which aims to bring natural language recognition to the often inscrutable phone menus that many companies still use today (disclaimer: TechCrunch is part of the Verizon Media Group). For Google, that’s a major win, but it’s also a chance for the Google Cloud team to highlight some of the work it has done in this area. It’s also worth noting that the Contact Center AI product is a good example of Google Cloud’s strategy of packaging up many of its disparate technologies into products that solve specific problems.

“A big part of our approach is that machine learning has enormous power but it’s hard for people,” Google Cloud CEO Thomas Kurian told me in an interview ahead of today’s announcement. “Instead of telling people, ‘well, here’s our natural language processing tools, here is speech recognition, here is text-to-speech and speech-to-text — and why don’t you just write a big neural network of your own to process all that?’ Very few companies can do that well. We thought that we can take the collection of these things and bring that as a solution to people to solve a business problem. And it’s much easier for them when we do that and […] that it’s a big part of our strategy to take our expertise in machine intelligence and artificial intelligence and build domain-specific solutions for a number of customers.”

The company first announced Contact Center AI at its Cloud Next conference two years ago and it became generally available last November. The promise here is that it will allow businesses to build smarter contact center solutions that rely on speech recognition to provide customers with personalized support while it also allows human agents to focus on more complex issues. A lot of this is driven by Google Cloud’s Dialogflow tool for building conversational experiences across multiple channels.

The coming two decades are scheduled to be very interesting decades for human space exploration and colonization. One of the things on America’s agenda for space exploration is creating humanity’s first Mars base, which will most likely happen in the 2030s and 2040s. If you are interested in what this Moon base will look like, please take a look at this video!

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SoftBank CEO Masayoshi Son’s Vision Fund has been impossible to ignore since its inception, pumping billions upon billions of dollars into tech companies like WeWork and Uber. Now, a string of high-profile losses and the coronavirus pandemic have put the fund deeply in the red. Bloomberg journalists Pavel Alpeyev, Sarah McBride and Tim Culpan break down the controversial investment strategies that have led to this critical moment for Son’s unprecedented fund.

Video by vicky feng and alan jeffries

Continue reading “The Troubled Saga of Masa Son’s $100 Billion Fund” »

In fact, in a recent paper in Royal Society Open Science, researchers showed that AI tasked with maximizing returns is actually disproportionately likely to pick an unethical strategy in fairly general conditions. Fortunately, they also showed it’s possible to predict the circumstances in which this is likely to happen, which could guide efforts to modify AI to avoid it.

The fact that AI is likely to pick unethical strategies seems intuitive. There are plenty of unethical business practices that can reap huge rewards if you get away with them, not least because few of your competitors dare use them. There’s a reason companies often bend or even break the rules despite the reputational and regulatory backlash they could face.

Those potential repercussions should be of considerable concern to companies deploying AI solutions, though. While efforts to build ethical principles into AI are already underway, they are nascent and in many contexts there are a vast number of potential strategies to choose from. Often these systems make decisions with little or no human input and it can be hard to predict the circumstances under which they are likely to choose an unethical approach.

Researchers from the UK and Switzerland have found a mathematical means of helping regulators and business police Artificial Intelligence systems’ biases towards making unethical, and potentially very costly and damaging choices.

The collaborators from the University of Warwick, Imperial College London, and EPFL – Lausanne, along with the strategy firm Sciteb Ltd, believe that in an environment in which decisions are increasingly made without human intervention, there is a very strong incentive to know under what circumstances AI systems might adopt an unethical strategy—and to find and reduce that risk, or eliminate entirely, if possible.

Artificial intelligence (AI) is increasingly deployed in commercial situations. Consider for example using AI to set prices of insurance products to be sold to a particular customer. There are legitimate reasons for setting different prices for different people, but it may also be more profitable to make certain decisions that end up hurting the company.

It is often said that the 21st century will belong to China because China will grow its military, develop its economy, and completely integrate Hong Kong. However, in this video, I argue that the 21st Century won’t belong to China because it won’t take advantage of space resources and because it will attempt to grab more than it can chew in its ambitious endeavors.

PS: The stock footage from this photo comes from Videvo!

Continue reading “Why the 21st Century Won’t Belong to China” »

Artificial intelligence (AI) is transforming how enterprises analyze and process information. It is also shifting from theoretical to real-world technology. Companies are deploying AI technologies to boost efficiency, reduce costs, and grow sales and profitability. The technology can also reduce marketing waste by predicting what works. It is the most impactful innovation of our lifetime, and it will create new winners and losers across entire industries.

According to Gartner, artificial intelligence will create $2.9 trillion in business value and 6.2 billion hours of worker productivity globally in 2021. Most of that value will be realized by enterprises that implement AI in functions such as sales management, customer service, manufacturing, and logistics. With improvements in natural language processing, employees and users can easily communicate with machine-learning interfaces.

Let’s look at how AI applications are revamping digital enterprises and the retail industry.

Elon Musk’s electric car business exceeds the value of almost every company in the S&P 500, including some iconic American companies.

Shares of Tesla (TSLA) were up 4% in midday trading Wednesday to a new record high of above $1,120 a share. At that price, Tesla’s market cap is nearly $210 billion.