The move is seen as a strategic way for Google to maintain its edge in the competitive AI industry and compete with OpenAI. By combining the talent and resources of both entities, Google DeepMind aims to accelerate AI advancements while maintaining ethical standards.

The new unit will be responsible for spearheading groundbreaking AI products and advancements, and it will work closely with other Google product areas to deliver AI research and products.

Google Research, the former parent division of Google Brain, will remain an independent division focused on “fundamental advances in computer science across areas such as algorithms and theory, privacy and security, quantum computing, health, climate and sustainability, and responsible AI.”

Demis Hassabis, CEO of DeepMind, believes that the consolidation of the two AI research labs will bring together world-class talent in AI with the computing power, infrastructure, and resources to create the next generation of AI breakthroughs and products boldly and responsibly.

Hassabis claims that the research accomplishments of Google Brain and DeepMind have formed the foundation of the current AI industry—ranging from deep reinforcement learning to transformers. The newly consolidated unit will build upon this foundation to create the next generation of groundbreaking AI products and advancements that will shape the world.

Over the years, Google and DeepMind have jointly developed several groundbreaking innovations. The duo’s achievements include AlphaGo – which famously beat professional human Go players – and AlphaFold, an exceptional tool that accurately predicts protein structures.

Other noteworthy achievements include word2vec, WaveNet, sequence-to-sequence models, distillation, deep reinforcement learning, and distributed systems and software frameworks like TensorFlow and JAX. These cutting-edge tools have proven highly effective for expressing, training, and deploying large-scale ML models.

Google’s acquisition of DeepMind for $500 million in 2014 paved the way for a fruitful collaboration between the two entities. With the consolidation of Google Brain and DeepMind into Google DeepMind, Google hopes to further advance its AI research and development capabilities.

Google’s chief scientist, Jeff Dean, will take on an elevated role as chief scientist for both Google Research and Google DeepMind. He has been tasked with setting the future direction of AI research at the company, as well as heading up the most critical and strategic technical projects related to AI, including a series of powerful multimodal AI models.

The creation of Google DeepMind underscores Google and parent company Alphabet’s commitment to furthering the pioneering research of both DeepMind and Google Brain. With the race to dominate the AI space becoming more intense, Google DeepMind is poised to accelerate AI advancements and create groundbreaking AI products and advancements that will shape the world.

(Image Credit: Google DeepMind)

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Ian Goodfellow is a renowned machine learning researcher. Goodfellow invented generative adversarial networks (GANs), developed a system for Google Maps that transcribes addresses from Street View car photos, and more.

In a departure note to his team at Apple, Goodfellow cited the company’s much-criticised lack of flexibility in its work policies.

Many companies were forced into supporting remote work during the pandemic and many have since decided to keep flexible working due to the recruitment advantages, mental/physical health benefits, lowering the impact of rocketing fuel costs, improved productivity, and reduced office space costs.

Apple planned for employees to work from the office on Mondays, Tuesdays, and Thursdays, starting this month. However, following backlash, on Tuesday the company put the plan on hold—officially citing rising Covid cases.

Goodfellow already decided to hand in his resignation and head to a company with more forward-looking, modern working policies.

The machine learning researcher had worked for Apple since 2019. Prior to Apple, Goodfellow had previously worked for Google as a senior research scientist.

Goodfellow is now reportedly returning to Google, albeit to its DeepMind subsidiary. Google is currently approving requests from most employees seeking to work from home.

More departures are expected from Apple if it proceeds with its return-to-office mandate.

“Everything happened with us working from home all day, and now we have to go back to the office, sit in traffic for two hours, and hire people to take care of kids at home,” a different former Apple employee told Bloomberg.

Every talented AI researcher like Goodfellow that leaves Apple is a potential win for Google and other companies.

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LinkedIn co-founder Reid Hoffman is joining Suleyman on the venture.

“Reid and I are excited to announce that we are co-founding a new company, Inflection AI,” wrote Suleyman in a statement.

“Inflection will be an AI-first consumer products company, incubated at Greylock, with all the advantages and expertise that come from being part of one of the most storied venture capital firms in the world.”

Dr Karén Simonyan, another former DeepMind AI expert, will serve as Inflection AI’s chief scientist and its third co-founder.

“Karén is one of the most accomplished deep learning leaders of his generation. He completed his PhD at Oxford, where he designed VGGNet and then sold his first company to DeepMind,” continued Suleyman.

“He created and led the deep learning scaling team and played a key role in such breakthroughs as AlphaZero, AlphaFold, WaveNet, and BigGAN.”

Inflection AI will focus on machine learning and natural language processing.

“Recent advances in artificial intelligence promise to fundamentally redefine human-machine interaction,” explains Suleyman.

“We will soon have the ability to relay our thoughts and ideas to computers using the same natural, conversational language we use to communicate with people. Over time these new language capabilities will revolutionise what it means to have a digital experience.”

Interest in natural language processing is surging. This month, Microsoft completed its $19.7 billion acquisition of Siri voice recognition engine creator Nuance.

Suleyman departed Google in January 2022 following an eight-year stint at the company.

While at Google, Suleyman was placed on administrative leave following bullying allegations. During a podcast, he said that he “really screwed up” and was “very sorry about the impact that caused people and the hurt people felt.”

Suleyman joined venture capital firm Greylock after leaving Google.

“There are few people who are as visionary, knowledgeable and connected across the vast artificial intelligence landscape as Mustafa,” wrote Hoffman, a Greylock partner, in a post at the time.

“Mustafa has spent years thinking about how technological advances impact society, and he cares deeply about the ethics and governance supporting new AI systems.”

Inflection AI was incubated by Greylock. Suleyman and Hoffman will both remain venture partners at the company.

Suleyman promises that more details about Inflection AI’s product plans will be provided over the coming months.

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The company selected 10 contests that were hosted on Codeforces – a programming competition platform with thousands of participants – to evaluate the performance of AlphaCode.

Below is an example of a problem #AlphaCode can successfully solve, using the exact information seen on @codeforces, & the program that #AlphaCode writes.

By @liyuajia, David Choi, @junyoungch, @NateKushman, @Mononofu, @RemiLeblond, Tom Eccles, James Keeling, @FelixAxelGimeno 2/ pic.twitter.com/TJu0Va46OS

— DeepMind (@DeepMind) February 2, 2022

Following the simulations, AlphaCode ranked in the top 54 percent of competitors. That means it wasn’t yet able to beat leading human programmers but could rival the average.

Mike Mirzayanov, Founder of Codeforces, said:

“I can safely say the results of AlphaCode exceeded my expectations. I was sceptical because even in simple competitive problems it is often required not only to implement the algorithm, but also – and this is the most difficult part – to invent it.

AlphaCode managed to perform at the level of a promising new competitor. I can’t wait to see what lies ahead!”

AlphaCode uses transformer-based language models to generate code “at an unprecedented scale”. A preprint paper detailing AlphaCode is available here (PDF).

Petr Mitrichev, Software Engineer at Google, commented:

“Solving competitive programming problems is a really hard thing to do, requiring both good coding skills and problem-solving creativity in humans.

I was very impressed that AlphaCode could make progress in this area and excited to see how the model uses its statement understanding to produce code and guide its random exploration to create solutions.”

DeepMind has released its dataset of competitive programming problems and solutions on GitHub to help others build on their results.

Ian Funnell, Manager of Developer Relations at Matillion, said:

“Advancements like AlphaCode are welcomed and represent huge progress in designing algorithms more effectively. AI coding in general empowers developers to pursue innovation and creativity in setting the parameters and goals, leaving the AI to actually execute them.

Ultimately, this is a catalyst for innovation—helping humans rather than replacing them. Developers are extremely capable individuals, and businesses will continue to count on them to reap valuable insights from their data to differentiate and compete.”

DeepMind has set up an interactive site to view some of AlphaCode’s solutions and dive into the model at alphacode.deepmind.com.

(Image Credit: DeepMind)

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Suleyman co-founded AI giant DeepMind alongside Demis Hassabis and Shane Legg in 2010 before it was acquired by Google in 2014 for $500 million.

DeepMind has become somewhat of an AI darling and has repeatedly made headlines for creating neural networks that have beat human capabilities in a range of games. DeepMind’s AlphaGo even beat Go world champion Lee Sedol in a five-game match.

While at DeepMind, Suleyman was the company’s head of applied AI. He left for Google in 2019 and was most recently the company’s vice president of AI product management and policy.

Suleyman’s career at Google has been somewhat of a rollercoaster.

Suleyman was once placed on administrative leave from Google following bullying allegations. On a podcast earlier this week, Suleyman said that he “really screwed up” and was “very sorry about the impact that caused people and the hurt people felt.”

However, Suleyman has also been praised by many after taking a principled stand against Google’s contract with the US Department of Defense.

Google ended up backing out from that particular initiative – dubbed ‘Project Maven’ – following the backlash it received. The company has recently caused another stir when it announced in November that it would be bidding for the Pentagon’s Joint Warfighting Cloud Capability contract.

Suleyman is joining venture capital firm Greylock Partners where his knowledge of AI is sure to be welcome in helping to determine the companies likely to become the next DeepMind.

“There are few people who are as visionary, knowledgeable and connected across the vast artificial intelligence landscape as Mustafa,” wrote Greylock Partner Reid Hoffman in a post. 

“At Greylock, Mustafa will spend his time advising early-stage companies and investing in promising startups in the AI space.”

Whether Google’s plan to bid for a new military contract played a factor in Suleyman’s decision to move on is unknown, but the timing seems more than coincidental.

In his post, Hoffman noted Suleyman’s moral code: “Mustafa has spent years thinking about how technological advances impact society, and he cares deeply about the ethics and governance supporting new AI systems.”

Google hasn’t always had the best track record when it comes to ethics. After acquiring DeepMind, Google established an ethics board for AI research but hasn’t revealed who actually sits on it.

One early version of Google’s AI ethics board featured right-wing conservative Kay James who is president of the Heritage Foundation. The Heritage Foundation has a history of opposing LGBTQ and immigrant rights.

News of Google’s latest defence contract bid might have been enough to push Suleyman into packing his bags.

(Image Credit: Joi Ito. Licensed under CC BY 2.0)

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The London-based firm recorded a profit of £43.8 million in 2020 with revenue at £826 million, according to its annual results filing with Companies House.

In previous years, DeepMind have posted losses well into the hundreds of millions that Alphabet has heavily subsidised. For example, the company lost £476 million in 2019 and has made cumulative losses of nearly £2 billion since 2014.

How the company has more than tripled its revenue from £265 million in 2019 to £826 million in 2020 remains somewhat of a mystery. No explanation has been provided by DeepMind.

There is of course the host of companies that fall under the Alphabet umbrella which DeepMind sells software and services to, namely YouTube, Google, and X. However, aside from this, the research lab sells no products to consumers and has not announced any partnerships publicly.

An industry insider told CNBC that the revenue jump could be down to “creative accounting”.

“I don’t think DeepMind have many or any revenue streams,” the source said, “so all that income is based on how much Alphabet pays for internal services, and that can be entirely arbitrary.”

On the other hand, a DeepMind spokesperson said the company made “significant progress” last year.

“Our groundbreaking results in protein structure prediction were heralded as one of the most significant contributions AI has made to advancing scientific knowledge,” the spokesperson said. “We’re excited to build on this success as we head into next year.”

The company has also been in the news recently for less savoury reasons, having just been hit with a class-action lawsuit following its handling of private NHS data in 2015.

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Google-owned DeepMind was quietly given the personal records of 1.6 million patients at the Royal Free London NHS Foundation Trust.

DeepMind said that it was using the data to create a potentially life-saving app called Streams. The app was designed to alert, diagnose, and detect when patients were at risk of developing acute kidney injury. It’s currently in the process of being decommissioned.

Several investigations were launched, including by the Information Commission that said in 2017 the hospital had not done enough to protect the privacy of patients when it shared data with Google.

Following that ruling, DeepMind apologised and said that it should have been thinking about the needs of patients rather than on building tools for clinicians.

The new case is being handled by law firm Mishcon de Reya on behalf of the lead plaintiff Andrew Prismall and the over 1.5 million other affected patients.

Mr Prismall said: “Given the very positive experience of the NHS that I have always had during my various treatments, I was greatly concerned to find that a tech giant had ended up with my confidential medical records.

“As a patient having any sort of medical treatment, the last thing you would expect is your private medical records to be in the hands of one of the world’s biggest technology companies.

“I hope that this case will help achieve a fair outcome and closure for all of the patients whose confidential records were obtained in this instance without their knowledge or consent.”

In the UK, such cases are “opt-out” which means all impacted parties will be included in the action unless they specifically request not to be. Given the size of the action, the overall payout for DeepMind could be large but small for each individual.

The case is just one of a growing number of high-profile cases around data collection in recent years. In April, Anne Longfield, the former Children’s Commissioner for England, filed a case against TikTok on behalf of millions of UK children over how the app collected and used their data.

Data collection is vital for training AIs that could very well save lives. However, individual privacy is also important.

Mishcon Partner Ben Lasserson, who is leading the DeepMind case, said: “This important claim should help to answer fundamental questions about the handling of sensitive personal data and special category data.

“It comes at a time of heightened public interest and understandable concern over who has access to people’s personal data and medical records and how this access is managed.”

As the UK leaves the EU it is looking to change its data laws. While the EU’s laws have often been criticised as being too strict and leaving innovation to happen outside of Europe, there are concerns that the UK could become too relaxed despite ministers’ pledges not to.

“There’s an opportunity for us to set world-leading, gold standard data regulation which protects privacy, but does so in as light-touch a way as possible,” said Culture Secretary Oliver Dowden.

Britain’s data watchdog is also getting a shakeup and will be led by John Edwards, New Zealand’s current privacy commissioner.

“There is a great opportunity to build on the wonderful work already done and I look forward to the challenge of steering the organisation and the British economy into a position of international leadership in the safe and trusted use of data for the benefit of all,” commented Edwards.

Only time will tell if the UK manages to strike a balance between the strictness of the EU and the somewhat laissez-faire approach taken by many of the world’s powers. However, the cases against DeepMind and others show that a modernisation of laws and thinking is needed to unlock the potential of AI to improve/save lives while protecting individual privacy.

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Last year, the organisers of the biennial Critical Assessment of protein Structure Prediction (CASP) recognised AlphaFold as a solution to the grand challenge of figuring out what shapes proteins fold into.

Professor John Moult, Co-founder and Chair of CASP, University of Maryland, said:

“We have been stuck on this one problem – how do proteins fold up – for nearly 50 years.

To see DeepMind produce a solution for this, having worked personally on this problem for so long and after so many stops and starts, wondering if we’d ever get there, is a very special moment.”

AlphaFold is a major scientific advance that will play a crucial role in helping scientists to solve important problems such as the protein misfolding associated with diseases such as Alzheimer’s, Parkinson’s, cystic fibrosis and Huntington’s disease.

Arthur D. Levinson, Founder and CEO of Calico, explained:

“AlphaFold is a once-in-a-generation advance, predicting protein structures with incredible speed and precision.

This leap forward demonstrates how computational methods are poised to transform research in biology and hold much promise for accelerating the drug discovery process.”

Using AI, AlphaFold has successfully predicted the structure of nearly all 20,000 proteins expressed by humans. An independent benchmark proved the system was capable of predicting the shape of a protein to a decent standard around 95 percent of the time.

DeepMind is now releasing its database of every single protein in the human body, as well as for the proteins of 20 additional organisms that scientists rely on for their research, for free, for any researchers to use for the betterment of humankind.

“This will be one of the most important datasets since the mapping of the Human Genome,” said Ewan Birney, Deputy Director-General of EMBL and Director of EMBL-EBI.

Thanks to the “astonishingly accurate” models produced by AlphaFold, Professor Andrei Lupas, Director of the Max Planck Institute for Developmental Biology, claims they were able to solve a protein structure they were stuck on for close to a decade.

The full AlphaFold protein structure database can be accessed for free online here.

(Photo by Carolina Garcia Tavizon on Unsplash)

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Google acquired DeepMind for $400 million in 2014 and the firm became a subsidiary of Google’s parent company Alphabet in 2015.

Suleyman co-founded DeepMind and originally became its chief product officer. After Google’s acquisition in 2014, Suleyman became DeepMind’s head of applied AI.

In a tweet, Suleyman announced he’s now moving to Google itself to work on AI policy alongside Ken Walker, Jeff Dean, and others.

Suleyman is a longstanding proponent for AI ethics, so his presence at Google may help to ensure the web giant pushes boundaries in terms of technology but while respecting things like human rights.

Of course, DeepMind’s work hasn’t been without its controversies.

An app called Streams, developed by DeepMind for doctors and nurses, was ruled by the UK government in 2017 to have gained inappropriate access to medical data from 1.6 million patients.

At the time, Suleyman wrote in a blog post:

“DeepMind operates autonomously from Google, and we’ve been clear from the outset that at no stage will patient data ever be linked or associated with Google accounts, products or services.”

Critics believe this promise was broken when Streams was grabbed by Google itself. One thing which can’t be criticised, however, is DeepMind has shown its ability to get working AI solutions into the market. Suleyman appears to be part of Google’s desire to tap some of DeepMind’s ability to ship working AI solutions.

In a blog post, DeepMind co-founder Demis Hassabis spoke highly of the role Suleyman had played at the firm:

“As a serial entrepreneur, Mustafa played a key role over the past decade, helping to get DeepMind off the ground, and launched a series of innovative collaborations with Google to reduce energy consumption in data centres, improve Android battery performance, optimise Google Play, and find ways to improve the lives of patients, nurses and doctors alike,” he said.

“Mustafa leaves DeepMind having helped set us up for long-term success, and I’m looking forward to what he’ll achieve in the years ahead as he joins Google in a new role.”

Suleyman will be starting his new role at Google in January.

(Image Credit: Mustafa Suleyman by Joi Ito under CC BY 2.0 license)

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The consortium includes Google DeepMind, Facebook AI, New York University, and the University of Washington. Each of the consortium’s members believe a more comprehensive benchmark is needed for NLP than current solutions.

The result is a benchmarking platform called SuperGLUE which replaces an older platform called GLUE with a “much harder benchmark with comprehensive human baselines,” according to Facebook AI. 

SuperGLUE helps to put NLP abilities to the test where previous benchmarks were beginning to pose too simple for the latest systems.

“Within one year of release, several NLP models have already surpassed human baseline performance on the GLUE benchmark. Current models have advanced a surprisingly effective recipe that combines language model pretraining on huge text data sets with simple multitask and transfer learning techniques,” Facebook said.

In 2018, Google released BERT (Bidirectional Encoder Representations from Transformers) which Facebook calls one of the biggest breakthroughs in NLP. Facebook took Google’s open-source work and identified changes to improve its effectiveness which led to RoBERTa (Robustly Optimized BERT Pretraining Approach).

RoBERTa basically “smashed it,” as the kids would say, in commonly-used benchmarks:

“Within one year of release, several NLP models (including RoBERTa) have already surpassed human baseline performance on the GLUE benchmark. Current models have advanced a surprisingly effective recipe that combines language model pretraining on huge text data sets with simple multitask and transfer learning techniques,” Facebook explains.

For the SuperGLUE benchmark, the consortium decided on tasks which meet four criteria:

1. Have varied formats.
2. Use more nuanced questions.
3. Are yet-to-be-solved using state-of-the-art methods.
4. Can be easily solved by people.

The new benchmark includes eight diverse and challenging tasks, including a Choice of Plausible Alternatives (COPA) causal reasoning task. The aforementioned task provides the system with the premise of a sentence and it must determine either the cause or effect of the premise from two possible choices. Humans have managed to achieve 100 percent accuracy on COPA while BERT achieves just 74 percent.

Across SuperGLUE’s tasks, RoBERTa is currently the leading NLP system and isn’t far behind the human baseline:

You can find a full breakdown of SuperGLUE and its various benchmarking tasks in a Facebook AI blog post here.

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