Hello and welcome to another episode of AI buzz! Today we’ll be discussing the recent Google DeepMind announcement. Let’s get started.
The battle of Google vs. OpenAI continues to intensify. For OpenAI, the pressure is to remain on top whereas Google is feeling the heat to release a competitive product soon to catch them. In order to catch up, Google has merged two AI business units together to form one AI powerhouse.
This last week, Google DeepMind was announced which combines Google Brain and DeepMind together. Google’s new business aims to provide greater focus on AI development.
This episode dives into the battle between Google vs. OpenAI and we’ll get into what the recent announcement from Google means for the future of the company.
Google vs. OpenAI (00:45)
In November 2022, OpenAI released ChatGPT. Since then, ChatGPT has found its way into all facets of society. By many accounts, Google was caught off guard by how performant and popular ChatGPT has been.
Google announced the waitlist for their competitor, Google Bard, in March 2023. Bard has been in the conversation for this next generation of chatbots, though at least in my conversations, ChatGPT seems to be much more popular. There are no publicly available user metrics for Bard that I could find, while ChatGPT has reached over 100 million users.
Google has been feeling the pressure since November. News source, The Information, mentions that Bard internally and externally has had some problems. Sundar Pichai (soon·daar puh·chai), the CEO of Alphabet & Google, asked that teams move with the utmost urgency in generating new ways to use large language models. Onlookers saw the rushed Bard release on display publicly with the hiccups that were present during the initial release in March. However, Google is staying persistent and a reorganization effort into a more cohesive team might be just what they need.
Announcing Google DeepMind: The new brainchild (01:57)
On April 20th, Google officially announced on their blog that they are combining DeepMind and Google Brain. This means that there is no longer an internal battle of DeepMind vs. GoogleBrain but rather Google Deepmind vs. OpenAI and other competitors.
In the announcement, Pichai noted the achievements of Search, Youtube, and Gmail that have utilized AI to reach new heights. He also states that "the pace of progress is now faster than ever before." In order to develop AI systems rapidly and safely, a new team is needed.
The tech CEO hopes that by combining all of this talent into a singular focused team, Google will be able to accelerate the progress of their AI development. Importantly, Pichai noted that Google Research will continue along its current path, though without Google Brain.
Demis Hassabis, former CEO of DeepMind, will lead Google DeepMind in this new merger. Jeffrey Dean, the former lead of Google Brain, will be the chief scientist of Google DeepMind. This a nuanced and fascinating leadership change. The expertise that Hassabis brings on creating demo-ready products through DeepMind previously will be critical for the release of future AI products.
A statement released by the new Google DeepMind CEO captured many of these same points as Pichai’s announcement did. However, one additional point that Hassabis mentioned in his release was that with Google DeepMind there will be a new "Scientific Board" as he calls it. This board will "oversee research progress and direction of the unit."
To get an idea of how smooth this merger will be for these two entities, we need to dive into their completely separate roots and history.
The story behind Google Brain (03:38)
Google Brain was a subdivision of Google Research. Started in 2011, Google Brain was a product of Google X that spun up with AI greats Jeffrey Dean and Andrew Ng among others. After spinning out from X, Google Brain became a part of the much broader Google Research operation. Some of the most notable accomplishments of Google Brain were to develop the widely-used Tensorflow package and the Google Cloud AutoML platform.
Google Brain states on their website that they “believe that openly disseminating research is critical to a healthy exchange of ideas.” This point may be put into jeopardy as part of the new Google DeepMind. There is too much money on the line to win the chatbot race and I imagine Google will hold off on sharing their latest cutting edge research. In a few years maybe they’ll share some of the details of what they did.
The Brain team is primarily made up of academic researchers. This is important to note since, spending time completing a PhD myself, the best academic researchers can sometimes be oblivious to the difficulty of implementation for real software products. Another snippet that Google Brain mentions about their team is that “members are encouraged to set their own research goals.” I’m certain this will not be achievable when there is a hard deadline for the next chatbot release. Research often has a “it’ll take the time that it takes” mentality, which again, is not conducive for real-world releases.
DeepMind: a startup that dominated (05:06)
Deepmind is a different beast from Google Brain entirely. They started as an independent company by Demis Hassabis and Shane Legg. As entrepreneurs, Hassabis and Legg must have developed the skillset to think in terms of product and profitability.
This is in sharp contrast with Google Brain where there likely was not much pressure to always be profitable. Instead, they aimed to generate research that could be made profitable by adding it to software products sometime down the line.
DeepMind releases demos of their innovations, rather than the source code like Google Brain’s TensorFlow. Perhaps the most incredible innovation from Deepmind was AlphaGo. The Netflix documentary, AlphaGo, details DeepMind’s journey of developing and showing off their AI tech to the world. Equally impressive is AlphaStar, which learned how to play Starcraft 2 at an elite level.
Research still plays a major role at DeepMind, though they appear to be most focused on implementation.
So, how interconnected have the teams at DeepMind and Google Brain been previously?
Google Brain and DeepMind, even though they’ve been operated by the same parent company Alphabet, were completely separate not only in name but also in terms of collaboration. The Information's report, which I’ll link to in the description, states that the two business units "have seldom collaborated or shared computer code with one another." Additionally, they reported that there were "years of intense rivalry" between the two groups. These two divisions are now being forced to work together to take on one of their biggest challenges yet in building the next Google chatbot. This will be a make-or-break moment for the company.
Google Gemini (06:42)
In Sundar Pichai’s (soon·daar puh·chai) announcement of the merger, he described a "series of powerful, multimodal AI models" to be released in the near future that will keep Google competitive. It’s been leaked that Google may be calling the new model "Gemini" which will be separate from Google Bard.
So far, we can only guess what exactly will be going into these new models. It's common for technology companies to iterate on versions of their models until they're performant. OpenAI has iterated on versions of GPT until they had a language model that could be released as ChatGPT. Similarly, Google has numerous products that they can pull from. Among them is DeepMind's Sparrow that was released in September 2022. In the release, they put a particularly strong focus on how easily the chatbot could be tricked by users. They published figures that stated 78% of the time, Sparrow would return a factual answer supported with evidence whereas on the other hand, 8% of the time, the chatbot could be tricked. It is reassuring that they are paying attention to this reliability metric within their model.
As the new organizational structure gets put into place, we will see how the focused effort on Gemini turns out. Will it be released with better reception than the bungled Google Bard? With two giant AI businesses coming together, it will be a make-or-break moment for Google in its race to stay in the AI conversation.
