Monthly Archives: June 2017

Volvo is forming a new joint partnership with Autoliv, called Zenuity, with a focus on developing self-driving automotive software. The plan is to eventually get to the point where they can field self-driving cars for sale, based on Nvidias Drive PX in-car AI computing platform, by the not-so-distant target year of 2021.

Thats a tall order, but Nvidias Drive PX is already being used to power self-driving vehicles in road testing today, including Nvidias own demonstration vehicles. Volvo and Autolivs Zenuity will use Nvidias AI car compute groundwork as the basis for their own software development, with the hopes of speeding up the development progress of Volvos commercially-targeted autonomous vehicles.

The software that were doing with them will be in some cases unique to Volvo, explained Nvidias Senior Director of Automotive on call. But Autoliv also has the rights to make the software available to other automakers. I think were starting to see, in the industry, these types of collaborations, and the opportunity to leverage from Nvidia a lot of this great work as well.

Zenuity, as a new entity, will provide the resulting self-driving software from the partnership to Volvo directly, while Autoliv will also sell the same software to third-party OEMs using its existing supply channels and relationships. Its great news for Nvidia, too, since that means their PX platform will be a key ingredient for OEMs looking to implement the system in their own vehicles.

Autoliv, a longtime safety technology supplier for the automotive industry, has been working on active safety systems including radar, vision and other ADAS tech for quite some time. But the company says that Nvidias AI platform will help it take its own autonomous and driver assistance tech to the next level.

Volvo and Nvidia had previously partnered for Volvos Drive Me autonomous car pilot program, but this is the first time the two have announced a partnership aimed at commercial sales of vehicles.

Excerpt from:

Volvo and Autoliv aim to sell self-driving cars with Nvidia AI tech by 2021 - TechCrunch

There is a lot of money to be made from Artificial Intelligence. By one estimate, the market is projected to hit US$36.8 billion by 2025. Some of this money will undoubtedly go to social good, like curing illness, disease and infirmity. Some will also go to better understanding intractable social problems like wealth distribution, urban planning, smart cities, and more efficient ways to do just about everything. But the key word here is some.

Theres no shortage of people touting the untold benefits of AI. But once you look past the utopian/dystopian and techno-capitalist hyperbole, what we are left with is a situation where various stakeholders want to find new and exciting ways to part you from your money. In other words: its business, not personal.

While the immediate benefits of AI might be clear from a strategic business perspective, the longer term repercussions are not. Its not just that the future is impossible to predict, complex technologies are hard to control, and human values are difficult to align with computer code, its also that in the present its hard to hear the voices calling for temperance and judiciousness over the din of companies clamouring for market advantage.

This is neither a new nor recent phenomenon. Whether it was the social media boom, the smart phone revolution, or the commercialisation of the world wide web, if theres money to be made, entrepreneurs will try and make it. And they should. For better or worse, economic prosperity and stability depends on what brilliance can be conjured up by scientific minds.

But thats only one side of the coin. The flipside is that prosperity and stability can only be maintained if equally brilliant minds work together to ensure we have durable ways to govern these technologies, legally, ethically, and for the social good. In some cases, this might mean agreeing that there are simply certain things we should not do with AI; some things that profit should not be derived from. We might call this conscious capitalism but it is, in fact, now a societal imperative.

There are structural problems in how the AI industry is shaping up, and serious asymmetries in the work that is being done. Its all well and good for large companies invested in presenting themselves as the softer, cuddlier, but no less profitable, face of this new technological revolution to tout hashtags like #responsibleAI or #AIEthics. No rational person is object to either, but they should not distract from the fact that hashtags arent coherent policy. Effective policy costs money to research, devise, and implement and right now, there is not enough time, cash, brainpower and undivided attention being devoted to building the robust governance infrastructure that will be required to compliment this latest wave of technological terraforming.

There are people out there thinking the things that need to be thought and implemented on the law, policy and governance side, but they are being drowned out by the PR, social media influencers and marketing campaigns that want to turn a profit from AI, or tell you how they can help your company do so.

Ultimately, our reach exceeds our grasp. We are far better at building new, exciting and powerful technologies than we are at governing them. To an extent, this has always been the case with new technologies, but the gap between what we create and the extent we can control it is widening and deepening.

Over the course of my PhD, where I researched long term strategies for AI governance and regulation, I was offered some sage advice: If you want to ensure youre remembered as a fool, make predictions about the future. While I try and keep that in mind, I am going to go out on a limb: AI will fundamentally remake society beyond all imagination.

Our commitment to ensuring safe and beneficial AI should amount to more than hashtags, handshakes and changing the narrative. It should be internalised into the ethos of AI development. Technical research must go hand in hand with law and policy research on both the public and private side. With great power comes great shared responsibility and its about time we recognise that this is the best business model we have for AI going forward.

If we are going to try and socialise the benefits of AI across society as the familiar refrain goes we need to get serious about the distribution of money across the AI industry today. Public and private research and public engagement has a critical role to play in this, even if its easier (and cheaper) to co-opt it into in-house research. We need to build a robust government-led research infrastructure in the UK, Europe and beyond to meet head on the challenges AI and other tech will pose. This means we need to think about more than just about data protection, algorithmic transparency and bias.

We also need to get serious about how our legal and political institutions will need to adapt to meet the challenges of tomorrow. And they will need to adapt, just as they have proven able to do in the face of earlier technological changes, whether it was planes, trains, automobiles or computers. From legal personhood to antitrust laws, or criminal culpability to corporate liability, we are starting to confront the incommensurability of certain legal norms with the lived reality of the 21st century.

AI is a new type of beast. We cannot do governance as usual, which has meant waiting for the latest and greatest tech to appear and then frantically react to keep it in check. Despite protestations to the contrary, we must be proactive in engaging with AI development, not reactive. In the parlance of regulation, we need to think ex ante and not just ex post. The hands-off, we-are-just-a-platform-and-have-no-responsibility-here tone of Silicon Valley must be rejected once and for all.

If we are going to adapt our institutions to the 21st century we must understand how they have adapted before, and what can be done today to equip them for the challenges of tomorrow. These changes must be premised upon evidence; not fatalistic conceits about the machines taking over, not philosophical frivolity, not private interests. We need smart people on the law and policy side working with the smart people sitting at the keyboards and toiling in the labs at the companies where these engines of tomorrow are being assembled line by line. Some might see this as an unholy alliance, but it is, in fact, a noble goal.

The governance and regulation of AI is not a national issue; it is a global issue. The untold fortunes being poured into the technical side of AI research needs to start making its way into the hands of those devoted to understanding how we might best actualise the technology, and how we can in good conscience use it to solve problems where there is no profit to be made.

The risk we run is that AI research kick starts a new global arms race; one where finishing second is framed as tantamount to economic hari-kari. There is tremendous good that the AI industry can do to help change this, but so far these good intentions have not manifested themselves in ways conducive to building the robust law, policy and social-scientific infrastructure that must compliment the technical side. As long as this imbalance continues, be afraid. Be very afraid.

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AI could kickstart a new global arms race we need better ways to govern it before it's too late - The Conversation UK

As AI slowly seeps into various sectors, it was fairly inevitable that we would start to see the AI for X startups begin to appear. Thus AI for small business social media is now a thing, in the shape of PromoRepublic, a US/Finnish/Ukrainian startup which has now raised a $1.2M investment round.

More specifically, they bill themselves as a WIX for a small businesss social presence. So what does that mean? Effectively its a simple way to grow a small business with social media content.

Investors in this seed round include Peter Druckers daughter Cecily Drucker, Nick Bilogorskiy (the ex-chief malware expert at Facebook), angel investor Aviram Jenik, business modeling guru David Lottenbach, Finnish Funding Agency for Innovation Tekes, as well as Howzat Partners, Digital Future and Spring Capital VC firms.

So far they have 50,000 small and medium business owners registered on the platform. It competes with visual design companies like Canva, Stencil, Adobe Spark, and DIFM (do-it-for-me) companies like MainStreenHub, Boostability and RevLocal who do custom social content for SMBs. DIFM-companies tend to cost around $300 per month which is pricey for small businesses. PromoRepublic starts at $20 per month.

The platform helps small business owners understand what specific content to post for their specific business. So, when to post, how often, what copy, design, call to actions and hashtags to use on Facebook, Twitter, LinkedIn and Instagram. Then the user needs to make a final customization and approve content for the whole month. The platform has access to 100,000+ templates and images and is integrated with Hootsuite, HubSpot, Buffer, and Yext.

PromoRepublic will post automatically at the right time and frequency, thus doing the heavy lifting for SME/SMB business owners who really wouldnt know where to begin in terms of creating and sharing content about their business.

Given that most small business owners usually do their own social media, theyd probably happily drop $20 a month on a platform that came up with ideas they could use and approve every month. Goodbye social media consultants? This could well be the case, at least at this level.

More here:

PromoRepublic raises $1.2M for AI which creates social media for small businesses - TechCrunch

Volkswagen is working with Nvidia to expand its usage of its artificial intelligence and deep learning technologies beyond autonomous vehicles and into other areas of business, the two companies revealed today.

VW set up its Munich-based data lab in 2014. Last year it pushed on with the hiring ofProf. Patrick van der Smagt to lead a dedicated AI team that is tasked with taking the technology into areas such as robotic enterprise, or use of the technology in enterprise settings.

Thats the backdrop to todays partnership announcement. VW wants to use AI and deep learning to power new opportunities within its corporate business functions and, more widely, in the field of mobility services. As an example, the German car-maker said it is working on procedures to help optimize traffic flow in cities and urban areas, while it sees the potential forintelligent human-robot collaboration, too.

Artificial intelligence is the key to the digital future of the Volkswagen Group. We want to develop and deploy high-performance AI systems ourselves. This is why we are expanding our expert knowledge required. Cooperation with NVIDIA will be a major step in this direction,Dr. Martin Hofmann, CIO of the Volkswagen Group, said in a statement.

Beyond the work on VWs own brands, the car-maker and Nvidia are teaming up to help other startups in the automotive space. The VW Data Lab is opening a startup support program that is specialized on machine learning and deep learning with Nvidias help. The first batch will include five startups and start this fall. The duo are also reaching out to students with a Summer of Code camp that will begin soon.

Nvidia is already working with VW-owned Audi on self-driving cars which they are aiming to bring to market by 2020 but todays announcement is purely about the data potential and not vehicles themselves. VW did ink an agreement earlier this year to work with Nvidia to develop AI-cockpit services for its 12 automotive brands, but it is also working with rival chip firm Qualcomm on connected cars and smart in-car systems, too.

This VW hookup is one part of a triple dose of automotive-themed news updates from Nvidia today.

Separately, it announced that Volvo andAutoliv have committedto sell self-driving cars powered by its technology by 2021. Nvidia also signed up auto suppliersZF and Hella to build additional safety standards into its autonomous vehicle platform.

See the article here:

Volkswagen partners with Nvidia to expand its use of AI beyond autonomous vehicles - TechCrunch