Despite the tragic crash of one of Uber’s self-driving cars in Arizona last month, Uber CEO still believes autonomous vehicles have a future. He emphasised in a press conference this week that ‘autonomous (vehicles) at maturity will be safer’.
This week we saw progress in the autonomous vehicle space which show that we on the road to an autonomous future:
Do you think there’s a bright future in store for self-driving cars? Tweet with this link for your chance to win a free ticket to CogX London 2018 (11-12 June). You can buy tickets and learn more on the CogX website.
Read on to learn more about science experiments with AI, Checkr’s raising of $100M, the impact of AI on banking.
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Inside a lab at Carnegie Mellon University in Pittsburgh, a robot arm lifts a bottle filled with chemical reagents and carries it over a bank of test tubes, where it dispenses a precise number of drops into each one. The arm swivels, replaces the bottle, swivels again, and picks up another container. Gracelessly, tirelessly, the machine thrums on, carrying out test after test. The experiments are part of an ongoing project to determine the ideal chemical makeup for high-capacity electric car batteries.
Over the next few months, an artificial intelligence algorithm will gradually take over the planning of experiments based on the battery test runs. Once fully functioning, this robot graduate student will decide how to modify the concentrations of the ingredients it’s testing. “It’s automating not only the manual part of doing the experiment but also the planning part,” says Brian Storey, the Toyota Research Institutescientist leading the project.
Landon Starr (Clearlink) writes about how AI innovations aren’t possible without the right data and specialised data science staff who know how to use it. The following are four lessons that vanguard businesses have learned about the intersection between data and deep learning — lessons you can apply to your organisation as you layer in your own artificial intelligence algorithms.
You have the data you need, but aren’t using it yet
Creating new data is as important as using existing data
Data and information availability empowers autonomy
A growing number of companies are using Checkr, a San Francisco-based company that says it currently runs one million background checks per month for more than 10,000 customers, including, most newly, the car-share company Lyft, the services marketplace Thumbtack, and eyewear seller Warby Parker.
Investors are betting many more customers will come aboard, too. This morning, Checkr is announcing $100 million in Series C funding led by T. Rowe Price, which was joined by earlier backers Accel and Y Combinator.
In yesterday’s FT (paywall), Laura Noonan writes about how the banking industry is taking a cautious approach in spite of excitement about new technology. She discusses how almost every big name consultancy has published research on how AI will transform banking.
17 of the 18 banks they surveyed are already using AI in front office for everything from Citi’s Facebook messenger chatbot to UBS’s use of Amazon’s virtual assistant Alexa for customer service. Speaking about banks…we’d recommend Barclay’s recent report Robots at the gate: Human and technology at work
People are remarkably good at focusing their attention on a particular person in a noisy environment, mentally “muting” all other voices and sounds. Known as the cocktail party effect, this capability comes natural to us humans. However, automatic speech separation — separating an audio signal into its individual speech sources — while a well-studied problem, remains a
significant challenge for computers.
In “Looking to Listen at the Cocktail Party”, Google researchers present a deep learning audio-visual model for isolating a single speech signal from a mixture of sounds such as other voices and background noise. In this work, they are able to computationally produce videos in which speech of specific people is enhanced while all other sounds are suppressed. Their method works on ordinary videos with a single audio track, and all that is required from the user is to select the face of the person in the video they want to hear, or to have such a person be selected algorithmically based on context.
MinerEye has launched its Data Tracker solution, which automates the process for detecting, tracking, and securing sensitive assets. According to a MinerEye press release, it can be used with unstructured and dark data, and can be leveraged as part of compliant cloud migration.
“Companies cannot protect, manage or utilize information they can’t find,” MinerEye CEO and co-founder Yaniv Avidan said in the release. “Using our Interpretive AITM, MinerEye fuses computer vision and machine learning to track information at the byte and pixel level, which no other solution has achieved.”
The majority of links on Twitter are shared by bots, a term for accounts that use automation in place of human decision-making. That’s according to a study released this week by the Pew Research Center that found accounts using automation serve up an estimated 66 percent of links on Twitter.
Researchers used a list of 2,315 popular websites and studied about 1.2 million tweets with links to those sites over six weeks in 2017 to come up with their results.The Center conducted the study to better understand automation on social media — a phenomenon worth examining because technology is being wielded in unprecedented ways to shape public opinion and push political agendas