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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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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