On March 3 next year, TechCrunch will host the fourth annual TC Sessions: Robotics + AI at UC Berkeley’s Zellerbach Hall. This time around we’re adding a new twist to the incredible line-up of speakers, breakout sessions and Q&As: a pitch-off for early-stage companies in the robotics and AI space.
How it works: The night before the event, 10 startups, chosen through an online application process, will pitch at a private event with TechCrunch editors, main-stage speakers and industry experts. A panel of VC judges will select the top five teams to then pitch the next day on the main stage at TC Sessions: Robotics + AI.
It is a once in a lifetime opportunity for founders to get their company in front of the tier-one leaders and investors in the industry, as well as receive video coverage on TechCrunch. We expect 1,500 attendees at the show and tens of thousands online.
Extra treat: Each of the 10 startup team finalists will receive two free tickets to attend the show the next day.
Apply here by February 1. TechCrunch will review applications and notify companies by February 15 so the founders have time to prepare. So, what are you waiting for? Get some spotlight!
Not interested in the pitch-off but want to attend this fantastic, show? Grab your Early-Bird pass here before it’s too late!
Giving big tech companies power over the NHS or the climate crisis wont build a fairer world. But public ownership would, says author Nathalie Olah
We hear it said all the time, most recently in a national campaign for BT: Technology will save us. The slogan was plastered on billboards across the country as part of BTs new advertising campaign, linked to a UK-wide digital skills movement developed partly with Google. The sentiment is so ubiquitous that it even led to a dispute with a startup of a similar name. But in an era dominated by the big four (Google, Amazon, Facebook and Apple) the idea that tech will save us rings hollow, an example of utopian messaging being used to conceal the simple pursuit of profit.
Having proposed solutions to everything from food shortages to suicide prevention to climate breakdown, companies such as Google and Facebook two of the leading western companies in the artificial intelligence arms race claim theres almost nothing that cannot be tackled through tech. But there are reasons to be sceptical. These companies business models depend on the development of ever more complex algorithms, sustained by enormous quantities of data. This data is used to improve the algorithms but access to it is also sold to advertisers and third-party businesses.
Conquering new sources of data has therefore become their primary mission. And thats why theyre eyeing our public commons: telecommunications, energy and even urban space, which continuously generate enormous quantities of real-time data. In 2017, it was reported that Googles AI outfit DeepMind was in talks with the National Grid. DeepMinds founder, Demis Hassabis, expressed an interest in expanding technology similar to that used to minimise energy wastage at Google data centres where electricity usage had been cut by 15% across the energy grid. This is an improvement, of course, but as one of the main examples of how AI systems might be used to tackle climate change it is hardly inspiring.
It also neglects to mention that unprecedented access to our critical infrastructure and publicly generated data would be given to a US tech giant. The collaboration between DeepMind and the (privatised, shareholder-paying) National Grid has for now been abandoned for reasons that are unclear. A recent article in Forbes speculates that the two companies couldnt reach an agreement on costs and intellectual property rights, in perhaps the most telling example of big techs ambitions to boost revenues through the commandeering of national infrastructure. Could Googles recent engagement with BT be built on a similar ambition?
Giving tech giants the power to solve social problems would mean granting them an immense stake in almost everything that our society requires in order to function. Google is currently signing contracts with the NHS to process patient records, despite there being legal question marks over a similar arrangement with a London hospital a few years ago. Whats more, the climate crisis is a political, not a technological problem. Whatever improvements Google or Facebook could make to our infrastructure would still fall far short of solving it. And when environmental collapse stands to affect poorest communities the hardest, the question remains as to how an industry that drives extreme wealth inequality can really be said to help build a greener, more humane, world.
These companies are able to make it seem as though their sole ambition is to optimise and improve their systems for the greater good. But this rhetoric distracts us from the fact that they are ushering in a new kind of surveillance capitalism, whereby a small number of entities extract enormous amounts of wealth through their access to data that is generated by us, the public.
To ensure that we retain the control to manage these systems, and to avoid an unprecedented level of power and wealth being concentrated in the hands of a very small elite, our infrastructure urgently needs to be brought under state control. This is why the Green New Deal, backed by Alexandria Ocasio-Cortez in the US and taken up in the UK by the Labour party, is so important. Not only will the UK version pursue efforts to keep global average temperature rises below 1.5C, but by encompassing public ownership of energy companies it provides a democratic line of defence against the predations of Silicon Valley. Labours proposal to part-nationalise BT opens up a new front in this battle especially since the party is planning to help pay for it with a tax on big tech.
In the years to come, this will give the state a far stronger negotiating position on resources, both digital and physical, as well as on the practical applications of this potentially world-altering technology. It is absolutely essential that publicly powered technology is answerable to public power.
Technology of deploying drones in squadrons is in its infancy, but armed forces are investing millions in its development
As evening fell on Russias Khmeimim airbase in western Syria, the first drones appeared. Then more, until 13 were flashing on radars, speeding towards the airbase and a nearby naval facility.
The explosives-armed aircraft were no trouble for Russian air defences, which shot down seven and jammed the remaining six, according to the countrys defence ministry. But the failed attack in January last year was disturbing to close observers of drone warfare.
It was the first instance of a mass-drone attack and the highest number of drones that I believe weve seen non-state actors use simultaneously in a combat operation, says Paul Scharre, a defence analyst and author who studies the weaponisation of artificial intelligence.
The attempted attacks continued and in September the Russian army said it had downed nearly 60 drones around the Khmeimim base so far this year.
“AWS DeepComposer is a 32-key, 2-octave keyboard designed for developers to get hands on with Generative AI, with either pretrained models or your own,” AWS’ Julien Simon wrote in a blog post introducing the company’s latest machine learning hardware.
The keyboard is supposed to help developers learn about machine learning in a fun way, and maybe create some music along the way. The area involved in generating creative works in artificial intelligence is called “generative AI.” In other words, it helps you teach machines to generate something creative using “generative adversarial networks.”
“Developers, regardless of their background in ML or music, can get started with Generative Adversarial Networks (GANs). This Generative AI technique pits two different neural networks against each other to produce new and original digital works based on sample inputs. With AWS DeepComposer, you can train and optimize GAN models to create original music,” according to Amazon.
AWS DeepComposer keyboard
Developers can train their own machine learning models or use ones supplied by Amazon to get started. Either way, you create the music based on the model, tweak it in the DeepComposer console on the AWS cloud, then generate your music. If you wish, you can share your machine-generated composition on SoundCloud when you’re done.
This is the third machine learning teaching device from Amazon, joining the DeepLens camera introduced in 2017 and the DeepRacer racing cars introduced last year. It’s worth noting that this is just an announcement. The device isn’t quite ready yet, but Amazon is allowing account holders to sign up for a preview when it is.