Delphi Automotive Grabs NuTonomy; the Jostling Continues

In yet another acquisition move within the vehicular autonomy market, UK-based Delphi Automotive  has purchased Boston-based NuTonomy, to double its research staff and add compatible software systems for its Automated Mobility on-Demand (AMoD) solutions. Neither of these companies is as yet a major player within the autonomous automobile sector. Delphi Automotive PLC is a General Motors spinoff and NuTonomy is a Carnegie Mellon startup. Delphi’s fully autonomous solution, called the Centralized Sensing Localization and Planning (CSLP) system is planned for a 2019 launch. It is based on Blackberry OS and Delphi’s other recent acquisition Ottomatika’s software. Meanwhile, NuTonomy was founded in 2013 by long-time industry players, Dr. Karl Iagnemma and Dr. Emilio Frazzoli, and is developing a full stack autonomous drive software solution for the AMoD market. The result of the acquisition will be to combine NuTonomy ‘s hundred member team with Delphi’s hundred member team to double research staff in an area where skills are in extreme demand.

While this acquisition could raise Delphi to a higher level of visibility among major autonomous vehicle challengers, it also comes with important implications for the other industry players. Delphi and NuTonomy were pursuing different collaborations to achieve success. Delphi was in a partnership with the BMW and Intel/Mobileye but NuTonomy is allied with Nvidia–which some believe has a more mature autonomous software stack. Inevitably, this brings into the fray the ongoing competition between Intel and Nvidia over artificial intelligence processors and supporting software–particularly as industry awaits the upcoming Nvidia Xavier SOC which should become available in 2018.

NuTonomy’s employees will remain in Boston while Delphi remains in the United Kingdom—though it also has offices in Boston. Both have been running experiments. and have a presence, in Singapore. The combination leaves Delphi with self-driving operations in Boston, Boston, Pittsburgh, Singapore, Santa Monica, and Silicon Valley. Combined with NuTonomy efforts, Delphi will have 60 autonomous cars on the road by the end of 2017.

Another point of interest is that, as with Google’s Waymo, Delphi Automotive intends to split off the vehicle autonomy business in 2018. It will create two new standalone companies: Delphi Technologies to handle the powertrain business, looking at next generation vehicle propulsion systems based on electrification; and Aptiv, which will include Electronics & Safety and Electrical/Electronic Architecture—including the “brains” to drive vehicles. Separating the autonomous vehicle units in the current context makes sense due to the special dynamics of this sector. Smaller companies are being bought by larger companies to obtain resources and skills that are hard to amass in the current environment and separate companies are more easily integrated into the competitive alliances that will be necessary to incorporate an increasing range of specialized products and expertise.

According to Delphi’s President and Chief Executive Officer, Kevin Clark, “The combination of the nuTonomy and Ottomatika AD teams, along with Delphi’s industry-leading portfolio of perception systems and smart vehicle architecture solutions, further enhances our competitive position as the industry’s most formidable provider of autonomous mobility solutions.”

In short, the autonomous vehicle sector is likely to remain volatile for some time and the search for talent will continue until the next generation of engineers in AI solutions becomes available.

Intersection of Blockchain and AI: The Video

AI and Blockchain are both topics that have generated significant interest recently as these technologies are incorporated into business processes. As with all digital technologies, however, they are not discrete. Maturing technologies often converge to develop entirely new possibilities, and blockchain combined with AI could create some potent results in fintech, accountability, and in infrastructure.

The following videos look at this potential for convergence from several perspectives.

The videos are a mixture of talks, presentations and teaching material available under standard YouTube license, with landing page descriptions added. Minor edits have been made where necessary.

The Convergence of Blockchain and Artificial Intelligence (Patrick Schwerdtfeger)

Published on Sep 9, 2016

The fields of Blockchain and Artificial Intelligence are converging, and they will intersect soon. Artificial Intelligence and Machine Learning require vast amounts of data. That’s how they learn. Meanwhile, Blockchain allows for decentralized autonomous organizations which will soon involve hundreds of millions of people. Furthermore, platforms built on Blockchain technology will soon be powerful enough to support AI applications. At that point, AI could evolve very quickly and become, effectively, an unstoppable utility for the world’s population. No one knows exactly how this convergence will play out. Certainly, I do not either, but I know this is an exciting time and I plan on following the developments as they emerge. The results will most definitely affect us all.

Blockchains for Artificial Intelligence (PyData)

Published on Jul 26, 2017

This talk by Trent McConaghy describes the various ways in which emerging blockchain technologies can be helpful for machine learning / artificial intelligence work, from audit trails on data to decentralized model exchanges.

In recent years, big data has transformed AI, to an almost unreasonable level. Now, blockchain technology could transform AI too, in its own particular ways. Some applications of blockchains to AI are mundane yet useful, like audit trails on AI models. Some appear almost unreasonable, like AI that can own itself — AI DAOs (decentralized autonomous organizations) leading to the first AI millionaires. All of them are opportunities. Blockchain technologies — especially planet-scale ones — can help realize some long-standing dreams of AI and data folks.

Numerai – A Revolutionary Hedge Fund Built on Blockchain and AI (Epicenter)

Published on Jul 11, 2017

Numerai Founder Richard Craib discusses his radical project to build a hedge fund with network effects. Numerai manages its portfolio by giving its data in encrypted form to data scientists who compete to create the best predictions and get paid with cryptocurrencies. Numerai expects to radically alter the structure of the hedge fund and asset management industry.

Topics discussed in this Epicenter episode include:

  • Quantitative trading and the role of AI in investing
  • How Numerai uses crowdsourcing and AI to manage its portfolio
  • The function of Numerai’s own token Numeraire

Code is Not the Law: Blockchain Contracts and Artificial Intelligence (Aliensyntax)

Published on Oct 28, 2016

A presentation by Adam Kolber (Brooklyn Law School) from The Ethics of Artificial Intelligence conference that took place October 14-15, 2016. It was hosted by the NYU Center for Bioethics in conjunction with the NYU Center for Mind, Brain and Consciousness. Published by


Creativity by Machine, and Implications for Innovation: The Video

Creativity has always been a particular challenge to AI, and many have suggested that it will be a key differentiator between robotic capabilties and human. However, as we approach a deeper understanding of machine intelligence and intelligence in general, we need to refine our understanding of creativity. With innovation being a critical business requirement based on creative thought, developing a better model of AI creative processes and their implications is likely to become increasingly important.

At the present time, machine creativity is very limited. This does not mean that it will always be so.  Following is a set of videos looking at various approaches to the intersection of creativity, AI, and robotics.

(from BJ Dooley’s IT Toons,

The videos are a mixture of talks and teaching material available under standard YouTube license, with landing page descriptions added. Minor edits have been made where necessary.

How Computers are Learning to be Creative (TED)

Published on Jul 22, 2016

A talk by Blaise Agüera y Arcas.  “We’re on the edge of a new frontier in art and creativity — and it’s not human.”

Blaise Agüera y Arcas, principal scientist at Google, works with deep neural networks for machine perception and distributed learning. In this captivating demo, he shows how neural nets trained to recognize images can be run in reverse, to generate them. The results: spectacular, hallucinatory collages (and poems!) that defy categorization.

“Perception and creativity are very intimately connected,” Agüera y Arcas says. “Any creature, any being that is able to do perceptual acts is also able to create.”

Can Robots be Creative? (TED-Ed)

 Published on Mar 19, 2015

A partial lesson by Gil Weinberg, with animation by TOGETHER.

People have been grappling with the question of artificial creativity — alongside the question of artificial intelligence — for over 170 years. For instance, could we program machines to create high quality original music? And if we do, is it the machine or the programmer that exhibits creativity? Gil Weinberg investigates this creative conundrum.

Artificial Intelligence & Creativity: The Drum Documentary (The Drum)

Published on Oct 18, 2016

In a quest to understand the role of artificial intelligence (AI) in advertising, The Drum, in partnership with Teads, has unveiled a new documentary, The Automation of Creativity, shot in Tokyo, London and Amsterdam.

The 16-minute film explores how artificial intelligence is beginning to impact the creativity of advertising and the role of human creatives.

To date, artificial intelligence (AI) machines have been able to write poetry, drive cars and there is even talk of a machine possibly winning a Pulitzer one day.

Turning the focus on the ad industry, The Automation of Creativity film stars the world’s first artificial intelligence creative director, AI-CD ß, launched by McCann Erickson Japan.

Job Automation: Are Writers, Artists, and Musicians Replaceable? (Big Think)

Published on Jul 10, 2017
You’re probably reading this from either a smartphone or a laptop. It’s no small secret that the device you’re looking at can create works of art… if you put your mind to it. But therein lies the point that Andrew McAfee makes in this video: you need to put your own creativity into the computer for it to work. Interestingly enough, computers are pretty adept at creating architecture and music. This is largely because what is pleasing to the quote-unquote “Western aesthetic mind” is easy to replicate. Music follows a formula, as does pleasing architecture and design. But when AI tries to replicate the human condition, or relate in any way to emotions and feelings, that is where even the smartest computer brains fails. Great news for all us writers out there. Not so great for all the graphic designers, though!