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Excitement for The Europas Awards for European Tech Startups is heating up. Here is the first wave of speakers and judges — with more coming!

The Awards — which have been running for over 10 years — will be held on 25 June 2020 in London, U.K. on the front lawn of the Geffrye Museum in Hoxton, London — creating a fantastic and fun garden-party atmosphere in the heart of London’s tech startup scene.

TechCrunch is once more the exclusive media sponsor of the awards and conference, alongside The Pathfounder.

The application form to enter is here.

We’re scouting for the top late-stage seed and Series A startups in 22 categories.

You can nominate a startup, accelerator or venture investor that you think deserves to be recognized for their achievements in the last 12 months.

CLOSING DATE FOR APPLICATIONS: 25 March 2020

For the 2020 awards, we’ve overhauled the categories to a set that we believe better reflects the range of innovation, diversity and ambition we see in the European startups being built and launched today. This year we are particularly looking at startups that are able to address the SDGs/Globals Boals.

The Europas Awards
The Europas Awards results are based on voting by experts, experienced founders, hand-picked investors and the industry itself.

But the key to it is that there are no “off-limits areas” at The Europas, so attendees can mingle easily with VIPs.

Timeline of The Europas Awards deadlines:

Submissions now open!
25 March 2020 – Submissions close
14 April – Public voting begins
25 April – Public voting ends
8 June – Shortlist Announced
25 June – Awards evening, winners announced

Amazing networking

We’re also shaking up the awards dinner itself. There are more opportunities to network. Our awards ceremony this year will be in the setting of a garden/lawn party, where you’ll be able to meet and mingle more easily, with free-flowing drinks and a wide selection of street food (including vegetarian/vegan). The ceremony itself will last less than 45 minutes, with the rest of the time dedicated to networking. If you’d like to talk about sponsoring or exhibiting, please contact Claire Dobson on claire@thepathfounder.com

Instead of thousands and thousands of people, think of a great summer event with the most interesting and useful people in the industry, including key investors and leading entrepreneurs.

The Europas Awards have been going for the last 10 years, and we’re the only independent and editorially driven event to recognise the European tech startup scene. The winners have been featured in Reuters, Bloomberg, VentureBeat, Forbes, Tech.eu, The Memo, Smart Company, CNET, many others — and of course, TechCrunch.

• No secret VIP rooms, which means you get to interact with the speakers

• Key founders and investors attending

• Journalists from major tech titles, newspapers and business broadcasters

The Pathfounder Afternoon Workshops
In the afternoon prior to the awards we will be holding a special, premium content event, The Pathfounder, designed be a “fast download” into the London tech scene for European founders looking to raise money or re-locate to London. Sessions include “How to Craft Your Story”; “Term Sheets”; “Building a Shareholding Structure”; Investor Panel; Meet the Press; and a session from former Europas winners. Followed by the awards and after-party!

The Europas “Diversity Pass”
We’d like to encourage more diversity in tech! That’s why we’ve set aside a block of free tickets to ensure that pre-seed female and BAME founders are represented at The Europas. This limited tranche of free tickets ensures that we include more women and people of colour who are specifically “pre-seed” or “seed-stage” tech startup founders. If you are a women/BAME founder, apply here for a chance to be considered for one of the limited free diversity passes to the event.

Meet some of our first speakers and judges:


Anne Boden
CEO
Starling Bank
Anne Boden is founder and CEO of Starling Bank, a fast-growing U.K. digital bank targeting millions of users who live their lives on their phones. After a distinguished career in senior leadership at some of the world’s best-known financial heavyweights, she set out to build her own mobile bank from scratch in 2014. Today, Starling has opened more than one million current accounts for individuals and small businesses and raised hundreds of millions of pounds in backing. Anne was awarded an MBE for services to financial technology in 2018.


Nate Lanxon (Speaker)
Editor and Tech Correspondent
Bloomberg
Nate is an editor and tech correspondent for Bloomberg, based in London. For over a decade, he has particularly focused on the consumer technology sector, and the trends shaping the global industry. Previous to this, he was senior editor at Bloomberg Media and was head of digital editorial for Bloomberg.com in Europe, the Middle East and Africa. Nate has held numerous roles across the most respected titles in tech, including stints as editor of WIRED.co.uk, editor-in-chief of Ars Technica UK and senior editor at CBS-owned CNET. Nate launched his professional career as a journalist by founding a small tech and gaming website called Tech’s Message, which is now the name of his weekly technology podcast hosted at natelanxon.com.


Tania Boler
CEO and founder
Elvie
/> Tania is an internationally recognized women’s health expert and has held leadership positions for various global NGOs and the United Nations. Passionate about challenging taboo women’s issues, Tania founded Elvie in 2013, partnering with Alexander Asseily to create a global hub of connected health and lifestyle products for women.


Kieran O’Neill
CEO and co-founder
Thread
Thread makes it easy for guys to dress well. They combine expert stylists with powerful AI to recommend the perfect clothes for each person. Thread is used by more than 1 million men in the U.K., and has raised $35 million from top investors, including Balderton Capital, the founders of DeepMind and the billionaire former owner of Warner Music. Prior to Thread, Kieran founded one of the first video sharing websites at age 15 and sold it for $1.25 million at age 19. He was then CEO and co-founder of Playfire, the largest social network for gamers, which he grew to 1.5 million customers before being acquired in 2012. He’s a member of the Forbes, Drapers and Financial Times 30 Under 30 lists.


Clare Jones
Chief Commercial Officer
what3words
Clare is the chief commercial officer of what3words; prior to this, her background was in the development and growth of social enterprises and in impact investment. Clare was featured in the 2019 Forbes 30 under 30 list for technology and is involved with London companies tackling social/environmental challenges. Clare also volunteers with the Streetlink project, doing health outreach work with vulnerable women in South London.


Luca Bocchio
Principal
Accel
Luca Bocchio joined Accel in 2018 and focuses on consumer internet, fintech and software businesses. Luca led Accel’s investment in Luko, Bryter and Brumbrum. Luca also helped lead Accel’s investment and ongoing work in Sennder. Prior to Accel, Luca was with H14, where he invested in global early and growth-stage opportunities, such as Deliveroo, GetYourGuide, Flixbus, SumUp and SecretEscapes. Luca previously advised technology, industrial and consumer companies on strategy with Bain & Co. in Europe and Asia. Luca is from Italy and graduated from LIUC University.


Bernhard Niesner
CEO and c-founder
busuu
/> Bernhard co-founded busuu in 2008 following an MBA project and has since led the company to become the world’s largest community for language learning, with more than 90 million users across the globe. Before starting busuu, Bernhard worked as a consultant at Roland Berger Strategy Consultants. He graduated summa cum laude in International Business from the Vienna University of Economics and Business and holds an MBA with honours from IE Business School. Bernhard is an active mentor and business angel in the startup community and an advisor to the Austrian Government on education affairs. Bernhard recently received the EY Entrepreneur of the Year 2018 UK Awards in the Disruptor category.


Chris Morton
CEO and founder
Lyst
Chris is the founder and CEO of Lyst, the world’s biggest fashion search platform used by 104 million shoppers each year. Including over 6 million products from brands including Burberry, Fendi, Gucci, Prada and Saint Laurent, Lyst offers shoppers convenience and unparalleled choice in one place. Launched in London in 2010, Lyst’s investors include LVMH, 14W, Balderton and Accel Partners. Prior to founding Lyst, Chris was an investor at Benchmark Capital and Balderton Capital in London, focusing on the early-stage consumer internet space. He holds an MA in physics and philosophy from Cambridge University.


Husayn Kassai
CEO and co-founder
Onfido
/> Husayn Kassai is the Onfido CEO and co-founder. Onfido helps businesses digitally onboard users by verifying any government ID and comparing it with the person’s facial biometrics. Founded in 2012, Onfido has grown to a team of 300 across SF, NYC and London; received over $100 million in funding from Salesforce, Microsoft and others; and works with over 1,500 fintech, banking and marketplace clients globally. Husayn is a WEF Tech Pioneer; a Forbes Contributor; and Forbes’ “30 Under 30”. He has a BA in economics and management from Keble College, Oxford.

Read more: https://techcrunch.com/2020/02/26/meet-the-first-wave-of-speakers-enter-your-startup-for-the-europas-awards-25-june/

Googles artificial intelligence sibling DeepMind repurposes Go-playing AI to conquer chess and shogi without aid of human knowledge

AlphaZero, the game-playing AI created by Google sibling DeepMind, has beaten the worlds best chess-playing computer program, having taught itself how to play in under four hours.

The repurposed AI, which has repeatedly beaten the worlds best Go players as AlphaGo, has been generalised so that it can now learn other games. It took just four hours to learn the rules to chess before beating the world champion chess program, Stockfish 8, in a 100-game match up.

Q&A

What is AI?

Artificial Intelligence has various definitions, but in general it means a program that uses data to build a model of some aspect of the world. This model is then used to make informed decisions and predictions about future events. The technology is used widely, to provide speech and face recognition, language translation, and personal recommendations on music, film and shopping sites. In the future, it could deliver driverless cars, smart personal assistants, and intelligent energy grids. AI has the potential to make organisations more effective and efficient, but the technology raises serious issues of ethics, governance, privacy and law.

AlphaZero won or drew all 100 games, according to a non-peer-reviewed research paper published with Cornell University Librarys arXiv.

Starting from random play, and given no domain knowledge except the game rules, AlphaZero achieved within 24 hours a superhuman level of play in the games of chess and shogi [a similar Japanese board game] as well as Go, and convincingly defeated a world-champion program in each case, said the papers authors that include DeepMind founder Demis Hassabis, who was a child chess prodigy reaching master standard at the age of 13.

Its a remarkable achievement, even if we should have expected it after AlphaGo, former world chess champion Garry Kasparov told Chess.com. We have always assumed that chess required too much empirical knowledge for a machine to play so well from scratch, with no human knowledge added at all.

Computer programs have been able to beat the best human chess players ever since IBMs Deep Blue supercomputer defeated Kasparov on 12 May 1997.

Read more: https://www.theguardian.com/technology/2017/dec/07/alphazero-google-deepmind-ai-beats-champion-program-teaching-itself-to-play-four-hours

In a major breakthrough for artificial intelligence, AlphaGo Zero took just three days to master the ancient Chinese board game of Go … with no human help

Googles artificial intelligence group, DeepMind, has unveiled the latest incarnation of its Go-playing program, AlphaGo an AI so powerful that it derived thousands of years of human knowledge of the game before inventing better moves of its own, all in the space of three days.

Named AlphaGo Zero, the AI program has been hailed as a major advance because it mastered the ancient Chinese board game from scratch, and with no human help beyond being told the rules. In games against the 2015 version, which famously beat Lee Sedol, the South Korean grandmaster, in the following year, AlphaGo Zero won 100 to 0.

The feat marks a milestone on the road to general-purpose AIs that can do more than thrash humans at board games. Because AlphaGo Zero learns on its own from a blank slate, its talents can now be turned to a host of real-world problems.

At DeepMind, which is based in London, AlphaGo Zero is working out how proteins fold, a massive scientific challenge that could give drug discovery a sorely needed shot in the arm.

Match
Match 3 of AlphaGo vs Lee Sedol in March 2016. Photograph: Erikbenson

For us, AlphaGo wasnt just about winning the game of Go, said Demis Hassabis, CEO of DeepMind and a researcher on the team. It was also a big step for us towards building these general-purpose algorithms. Most AIs are described as narrow because they perform only a single task, such as translating languages or recognising faces, but general-purpose AIs could potentially outperform humans at many different tasks. In the next decade, Hassabis believes that AlphaGos descendants will work alongside humans as scientific and medical experts.

Previous versions of AlphaGo learned their moves by training on thousands of games played by strong human amateurs and professionals. AlphaGo Zero had no such help. Instead, it learned purely by playing itself millions of times over. It began by placing stones on the Go board at random but swiftly improved as it discovered winning strategies.

David Silver describes how the Go playing AI program, AlphaGo Zero, discovers new knowledge from scratch. Credit: DeepMind

Its more powerful than previous approaches because by not using human data, or human expertise in any fashion, weve removed the constraints of human knowledge and it is able to create knowledge itself, said David Silver, AlphaGos lead researcher.

The program amasses its skill through a procedure called reinforcement learning. It is the same method by which balance on the one hand, and scuffed knees on the other, help humans master the art of bike riding. When AlphaGo Zero plays a good move, it is more likely to be rewarded with a win. When it makes a bad move, it edges closer to a loss.

Demis
Demis Hassabis, CEO of DeepMind: For us, AlphaGo wasnt just about winning the game of Go. Photograph: DeepMind/Nature

At the heart of the program is a group of software neurons that are connected together to form an artificial neural network. For each turn of the game, the network looks at the positions of the pieces on the Go board and calculates which moves might be made next and probability of them leading to a win. After each game, it updates its neural network, making it stronger player for the next bout. Though far better than previous versions, AlphaGo Zero is a simpler program and mastered the game faster despite training on less data and running on a smaller computer. Given more time, it could have learned the rules for itself too, Silver said.

Q&A

What is AI?

Artificial Intelligence has various definitions, but in general it means a program that uses data to build a model of some aspect of the world. This model is then used to make informed decisions and predictions about future events. The technology is used widely, to provide speech and face recognition, language translation, and personal recommendations on music, film and shopping sites. In the future, it could deliver driverless cars, smart personal assistants, and intelligent energy grids. AI has the potential to make organisations more effective and efficient, but the technology raises serious issues of ethics, governance, privacy and law.

Writing in the journal Nature, the researchers describe how AlphaGo Zero started off terribly, progressed to the level of a naive amateur, and ultimately deployed highly strategic moves used by grandmasters, all in a matter of days. It discovered one common play, called a joseki, in the first 10 hours. Other moves, with names such as small avalanche and knights move pincer soon followed. After three days, the program had discovered brand new moves that human experts are now studying. Intriguingly, the program grasped some advanced moves long before it discovered simpler ones, such as a pattern called a ladder that human Go players tend to grasp early on.

AlphaGo Zero starts with no knowledge, but progressively gets stronger and stronger as it learns the game of Go. Credit: DeepMind

It discovers some best plays, josekis, and then it goes beyond those plays and finds something even better, said Hassabis. You can see it rediscovering thousands of years of human knowledge.

Eleni Vasilaki, professor of computational neuroscience at Sheffield University, said it was an impressive feat. This may very well imply that by not involving a human expert in its training, AlphaGo discovers better moves that surpass human intelligence on this specific game, she said. But she pointed out that, while computers are beating humans at games that involve complex calculations and precision, they are far from even matching humans at other tasks. AI fails in tasks that are surprisingly easy for humans, she said. Just look at the performance of a humanoid robot in everyday tasks such as walking, running and kicking a ball.

Tom Mitchell, a computer scientist at Carnegie Mellon University in Pittsburgh called AlphaGo Zero an outstanding engineering accomplishment. He added: It closes the book on whether humans are ever going to catch up with computers at Go. I guess the answer is no. But it opens a new book, which is where computers teach humans how to play Go better than they used to.

David Silver describes how the AI program AlphaGo Zero learns to play Go. Credit: DeepMind

The idea was welcomed by Andy Okun, president of the American Go Association: I dont know if morale will suffer from computers being strong, but it actually may be kind of fun to explore the game with neural-network software, since its not winning by out-reading us, but by seeing patterns and shapes more deeply.

While AlphaGo Zero is a step towards a general-purpose AI, it can only work on problems that can be perfectly simulated in a computer, making tasks such as driving a car out of the question. AIs that match humans at a huge range of tasks are still a long way off, Hassabis said. More realistic in the next decade is the use of AI to help humans discover new drugs and materials, and crack mysteries in particle physics. I hope that these kinds of algorithms and future versions of AlphaGo-inspired things will be routinely working with us as scientific experts and medical experts on advancing the frontier of science and medicine, Hassabis said.

Read more: https://www.theguardian.com/science/2017/oct/18/its-able-to-create-knowledge-itself-google-unveils-ai-learns-all-on-its-own