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From Creating Alphabet’s to Developing Novel Proteins: Salesforce’s Generative AI To Tackle Society’s Biggest Challenges

While artificial intelligence is ginormous and revolutionary, generative AI, let’s say is evolutionary and more promising. Salesforce‘s research team…



This article was originally published by AITHORITY

While artificial intelligence is ginormous and revolutionary, generative AI, let’s say is evolutionary and more promising. Salesforce‘s research team is constantly seeking new methodologies to solve problems across different societies, and society at large. This article is an attempt to understand how Salesforce’s partnership with an academic institution and a biomedical company can apply the AI language model.

On a global level, leaders across industries have whole-heartedly acknowledged and appreciated the possibilities Generative AI can bring to a company. The year 2022, can be christened as the year of Generative AI – when technology took the baton and created novel content in different formats and in a perfectly human-like tone.

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The Works of Nikhil Naik & the Salesforce Research Team

Generative AI is a hot-selling topic, courtesy, of innovative products like ChatGPT, which have been in the news ever since its launch in November 2022. Over the past few months, multiple articles have been written about its superpowers while some raised concerns over its ethical usage.

Be it writing songs, jokes, essays, articles, etc seems lucrative right now, but what’s intriguing and most likely will yield results is the work Salesforce’s research team headed by Nikhil Naik, Director Of AI Research, is doing. In the last 5 years, Naik’s team has been quietly and passionately working on some bigger applications.

The research team trained generative AI on conversational language, which was then shaped into a development code through a large-scale language model known as CodeGen.

AI for Society Initiative

Naik explained that the goal of the research team under the AI for Society initiative was simple – to be able to apply Salesforce AI on issues that are likely to have a bigger impact on society.

Through this initiative, the Salesforce Research work has been quite vivid ranging from incorporating computer vision to track great white sharks and identifying the correct treatment plan for breast cancer patients via artificial intelligence to implementing Ai for balanced economic policies.

Naik added that the team had an interesting way of working. They first identify the AI tools and techniques they excel in and then look out for problems where those AI techniques would work in a tailor-made fashion. This unique approach resulted in the creation of ProGen – an AI language model trained on the world’s largest protein database.

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Naik pointed out,

“AI models ingest a large amount of text and they learn to predict the next word that might come after a given word. And just by training using this pretty simple method, you can train an AI algorithm to generate very realistic language about any topic that you might be interested in. And what we realized is that the same technology can be applied to generating proteins.”

When an opportunity of developing novel proteins came through, the Salesforce Research team looked at the avenues it would open up like new medicines, vaccines, or sustainability innovations.

In 2020, Naik and his troop set out to work around the problem of protein design with the help of generative AI, especially large language models. The reason for choosing protein design was simple – it was a vast field with tremendous scope for invention and research, which meant, “accelerating the discovery of novel drugs and useful industrial chemicals.”

An Alphabet Using Amino Acids

At first, the Salesforce team went all creative and made an “alphabet” using nothing but amino acids. After all, what better way to build than using the building block of all proteins? Just the way “letters” come together to form proteins, similarly, you can train a large language model to not only predict the next word but also generate sentences in English. The team trained used a database of 280 million protein sequences to generate novel proteins and train a large language model.

Despite their excitement about the progress, Naik and the team did not have the bandwidth to test and ascertain if the AI language model for generating proteins could create something useful. To fight ambiguity, they partnered with the Fraser Lab at UCSF and medical startup Tierra Biosciences to examine their research.

First, the Salesforce Research team sent around 100 AI-generated proteins to synthesize to Tierra and create test tube versions of them. Tierra found that the proteins were functional, and so for further research, they were sent to the University of California San Francisco’s Fraser Lab. The lab drew comparisons between natural proteins and artificial proteins.

“The lab tests showed that we can design proteins that are 60-70% dissimilar to anything ever seen in nature, but that are still functioning proteins, containing biological activity. And that is an important scientific milestone for the future of drug discovery and industrial chemical design,” Naik said.

Another striking conclusion was that ‘ProGen-created proteins were 73% biologically active, whereas only 59% of naturally-occurring proteins were.’

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Using Technology Ethically

Having understood the intricacies of the work, Naik and his team, and practically anyone who was even remotely involved, knew that using this powerful technology ethically was of paramount importance.

Each and every step and process were thoroughly scrutinized by Salesforce’s Ethical AI Council and Office of Ethics under Salesforce’s Chief Ethical and Humane Use Officer, Paula Goldman to ensure ethical guidelines were followed and that Ai was deployed securely and responsibly.

Considering the limitless opportunities in this space and to further strengthen the ethical usage of the technology, Goldman and her teams decided to build on Trusted AI Principles to help guide the process. This was more critical in the case of ProGen, where there was a strong need for protocols to be put in place to “ensure safe usage and limitation of unintended harmful effects.”

Nikhil and his team are optimistic, and excited, yet modest about their ability to create new designs of proteins never-before-seen in nature, because of the fact that they can be used for medicine and other domains.

And the Journey Continues

Ever since the success of the mentioned experiments, researchers have been more than keen to build on his team’s work and also showcase the applications in different domains. With a hopeful wish, Nikhil stated that in the near future, there will most likely be a massive spike in research and commercial activity in this space. The journey seems to have started with Naik and his Salesforce AI Research team making every effort to identify potential treatments for rheumatoid arthritis, multiple sclerosis, and other neurological and autoimmune disorders by making the most of their work with ProGen.

What Naik and his team are doing earnestly, and the kind of approach they have is truly remarkable in every possible way. The question remains, can it be used somewhere else, in some other field or to address global challenges like food supply, sustainability, or climate change? Naik proudly says that this is where we can see unlock the true power of AI. As they say, the journey has just begun.

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Story input: Salesforce

The post From Creating Alphabet’s to Developing Novel Proteins: Salesforce’s Generative AI To Tackle Society’s Biggest Challenges appeared first on AiThority.


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