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A media feeding frenzy over the exploding scale and increasing costs of artificial intelligence (AI) has created a divide between the reality of the technology and its perception among decision makers, explained Silvio Savarese, Chief Scientist of Salesforce AI Research in a recent interview.
Whether these concerns come from worries about the bottom line, the impact of AI on the environment, or even basic questions of fairness and access, Savarese believes that changing these misconceptions requires an understanding of when scale is necessary to deliver high-quality AI outputs — and when it isn’t.
In the interview, Savarese also shared why the environmental and financial price tag of AI doesn’t have to be as head-spinning as the headlines might suggest, and how understanding the different scales and performance of AI models can help any business responsibly harness this transformative technology to boost productivity, build deeper relationships with customers, and enhance daily workflows and processes.
Rather than asking if the scale of today’s LLMs is necessary, let’s ask what it’s necessary for.
The scale and size of an AI deployment isn’t inherently advantageous. Rather, when implementing AI, there’s a range of possibilities and trade-offs that should be explored. Remember, the ChatGPTs of the world are designed to do more or less everything, and that makes them very different from most enterprise applications. They can help with homework, suggest holiday recipes, and even reimagine La bohème’s libretto as Socratic dialogues. It’s a great party trick — albeit an expensive one. Training Open AI’s ChatGPT 4 cost more than $100 million. But that isn’t what enterprises are using AI for.
The scale and size of an AI deployment isn’t inherently advantageous. Rather, when implementing AI, there’s a range of possibilities and trade-offs that should be explored.”
Silvio Savarese, Chief Scientist of Salesforce AI Research
There’s also the environmental impact of these large LLMs. The hypothetical long-term benefits of AI in combating climate change in areas such as monitoring emissions and optimizing the transportation of goods are significant, with the potential to reduce global emissions 5 to 10% by 2030. However, the utilization of LLMs, while groundbreaking in their capabilities, requires enormous computing resources, exacerbating pressing concerns such as the release of greenhouse gasses, the depletion of water resources, and the extraction of raw materials along the supply chain. Given the urgency of the climate crisis and the imperative to combat planet-warming emissions, it’s paramount that the development and implementation of AI technologies doesn’t surpass the capacity of our planet’s resources.
In contrast to LLMs like ChatGPT or Anthropic’s Claude, an AI model like our own CodeGen 2.5, has a limited set of tasks — helping developers write, understand, and debug code faster. Despite its deliberately small scale, its performance is on a par with models literally twice its size, boasting remarkable efficiency without compromising on utility. So even as it helps developers work faster, it also reduces costs, latency, and, crucially, environmental impact compared to larger-scale LLMs.
Businesses should not be asking whether they need scale, but how they want to apply that scale. Depending on the task, the answer may vary wildly — and bigger is most certainly not always better.
Believe it or not, even this isn’t a clear-cut answer. Large models do generally outperform their smaller counterparts when it comes to flexibility. But therein lies the nuance that is so often left out of conversations around LLMs: as tasks become more narrow, more well-defined, and more unique to a specific organization or domain — exactly what enterprise AI is all about — it’s possible to do more with less.
In other words, most models aren’t meant to be everything to everyone, which frees up enterprises to focus on their needs while saving huge amounts of resources in the process.
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Not all the time, no. But under the right circumstances, small models really can offer the best of all worlds: reduced cost, lower environmental impact, and improved performance. Small models are often neck-and-neck with large ones when it comes to tasks like knowledge retrieval, technical support, and answering customer questions.
Small models are often neck-and-neck with large ones when it comes to tasks like knowledge retrieval, technical support, and answering customer questions.”
Silvio Savarese, Chief Scientist of Salesforce AI Research
In fact, with the right strategy, they can even perform better. This includes models from the open-source world, including Salesforce’s own XGen 7B. Our model is specifically trained on a sequence of data with suitable length, helping it with tasks like the summarization of large volumes of text and even writing code — and it consistently exceeds the performance of larger models by leveraging better grounding strategies and better embeddings. Additional small-scale models from our AI research org are planned to be released soon and will be powering generative AI capabilities for critical customer use cases.
Scaling down models isn’t just about saving money. It’s one of the best ways to ensure AI outputs are reliable. Large models are exciting, but they often don’t provide much information about the data they use. This leaves companies with no choice but to monitor deployments closely to catch harmful or inaccurate outputs. Needless to say, this falls far short of the standard most businesses expect from their technology.
Scaling down models isn’t just about saving money. It’s one of the best ways to ensure AI outputs are reliable.”
Silvio Savarese, Chief Scientist of Salesforce AI Research
Instead, consider a simple, intuitive fact: smaller models are trained on smaller data sets, which are inherently easier to document and understand — an increasingly important trust and transparency measure as the role of LLMs grows to include mission-critical applications that don’t just require reliability, but accountability as well.
Additional steps for verifying that generative AI produces trusted results are of course, critical: the Einstein Trust Layer is Salesforce’s guaranteed accountability model assisting businesses in efficiently managing data privacy, security, and transparency. The Einstein Trust Layer serves as a secure middleman for user interactions with LLMs. Its functions include obscuring personally identifiable information (PII), monitoring output for harmful content, guaranteeing data privacy, prohibiting the storage or use of user data for future training, and unifying discrepancies among various model providers.
There are, of course, times when increasing scale is simply unavoidable, and the power of small models doesn’t negate the potential of bigger ones. But again, let’s ask the right questions: rather than simply asking whether we need scale, let’s ask what you need it for. The answer will inform your strategy from the very first steps, because there are, ultimately, two very different ways to scale: increasing the parameter count of a single model, or orchestration — the connection of multiple models into a single, larger deployment, analogous to multiple human workers coming together as a team.
Orchestration has the potential to offer the power of scale while still keeping its pitfalls in check. After all, even small models can do amazing things when combined with one another, especially when each is geared toward a specific strength that the others might lack: one model to focus on information retrieval, one to focus on user interactions, another to focus on the generation of content and reports, and so on. In fact, smaller models are arguably a more natural choice in such cases, as their specialized focus makes their role in the larger whole easier to define and validate.
In other words, small models can be combined to solve ever-bigger problems, all while retaining the virtues of their small size — each can still be cleanly trained, tuned, and understood with an ease large models can’t touch. And it’s yet another example of why a simple parameter count can often be misleading.
LLMs are a hugely complex topic, and there’s room for any number of voices in the conversation. But we’re overdue for a more balanced, strategic perspective on the question of how much we need to get what we want: how much time, how much compute, and, ultimately, how much cost. The answer isn’t anywhere near as simple as the impression one might get from the headlines, and I believe amazing things can be done on just about any budget. It’s just a matter of knowing what’s possible.
Today, Salesforce announced it has named Jason Yau as SVP and Architect, within the Office of the CEO. In his new role, Jason will partner deeply with Salesforce’s customers on their digital transformations and drive innovation in the Salesforce roadmap to further accelerate its position as the #1 AI CRM.
Jason is a seasoned, three-time CTO who has a proven track record leading successful B2C and commerce transformations. Most recently, he was the Global Enterprise CTO at Shopify and prior to that, he was CTO at Dollar Shave Club and SPARC Group (parent company of retail brands Eddie Bauer, Nautica, and Reebok among others).
At Salesforce, Jason will work with Fortune 500 customers spanning multiple industries. He’ll leverage the full breadth of the Salesforce Platform—as well as Data Cloud and Einstein 1 — to help customers with their large scale digital transformations.
Jason is a one-of-a-kind consumer visionary with an exceptional track record of technical innovation.
Kendall Collins, Chief Business Officer and Chief of Staff to the CEO
“Jason is a one-of-a-kind consumer visionary with an exceptional track record of technical innovation. By combining his unique skillset and perspective with the breadth of the Salesforce Platform, he will be able to help global brands transform their customer experiences with AI across Commerce, Marketing, Sales and Service,” said Kendall Collins, Chief Business Officer and Chief of Staff to the CEO. “Salesforce has an incredible opportunity ahead with AI and data, and I’m thrilled to partner with Jason to help drive this next phase of our growth.”
With its values driven culture, deep customer relationships and transformative Einstein 1 and Data Cloud technology, no company is better positioned to lead the AI and data revolution than Salesforce.
Jason Yau, SVP and Architect, Office of the CEO
“It’s a pivotal time for enterprise technology—every brand is looking to harness the power of AI and data at scale,” said Jason Yau, SVP and Architect, Office of the CEO. “With its values driven culture, deep customer relationships and transformative Einstein 1 and Data Cloud technology, no company is better positioned to lead the AI and data revolution than Salesforce. By joining Salesforce, I’ll be able to drive a much broader, deeper, and global impact for brands and I can’t wait to get started.”
The Massachusetts Department of Transportation (MassDOT) is working with Salesforce to deploy innovative technology systems that support internal collaboration, drive efficiencies in service delivery across various business divisions, and provide real-time visibility into different projects.
The impact: Massachusetts has one of the highest rates of public transit use in the United States, and MassDOT provides safe and reliable transportation for this volume of ridership with a strong focus on customer service. This starts with having scalable and future-proof technologies accessible to employees and constituents.
Go deeper: MassDOT has a number of divisions with different priorities, processes, and systems. The team needed to shift their focus away from legacy systems and migrate their business applications onto low-code/no-code configurable platforms. MassDOT launched a FedRAMP-authorized application development platform on Salesforce to optimize processes agency-wide and personalize the customer service experience across each of its business divisions, including the Registry of Motor Vehicles (RMV), Aeronautics, Planning and Enterprise Services, and Highway.
MassDOT perspective: “We’ve been using Salesforce’s government solutions to drive our own productivity. Salesforce’s built-in compliance lets us innovate quickly in a safe and secure environment so we can deliver highly-personalized services to the millions of constituents we serve.” – Anu Goutham, Deputy CIO of Information Technology
We’ve been using Salesforce’s government solutions to drive our own productivity. Salesforce’s built-in compliance lets us innovate quickly in a safe and secure environment so we can deliver highly-personalized services to the millions of constituents we serve.
Anu Goutham, Deputy CIO of Information Technology
Salesforce Perspective: “Modernization and innovation are top-of-mind for the public sector, and MassDOT was in need of consolidated, real-time systems that help create better collaboration across business divisions. By implementing these solutions, Salesforce will continue to help MassDOT drive greater efficiency and transparency for its employees and constituents.” – Nasi Jazayeri, EVP & GM, Public Sector
Editor’s note: This story is part of an ongoing series to spotlight our Equality Groups and how they serve Salesforce’s global employees. Check out additional interviews with the leaders of Salesforce Women’s Network, BOLDforce, and Faithforce.
To celebrate Earth Month, we spoke with Lindsey Peterson, Global President of Earthforce, Salesforce’s Equality Group dedicated to promoting and celebrating environmental responsibility. Here, Peterson shares why Earthforce’s 14,000 global members believe in being better people for the planet — and creating a better planet for all people.
I started at Salesforce in 2019 as a Recruiting Coordinator, and have since moved through different roles within our Employee Success organization. Most recently, I took on a role on the newly formed Talent Growth and Development team as a Talent Strategy and Design Manager. In this role, I get to work specifically on executive talent management and succession planning.
Earthforce was one of the reasons I joined Salesforce. I was transitioning out of higher education and wanted to find a company that was constantly innovating. Friends who worked at Salesforce told me about the company’s Equality Groups and commitment to giving back, which was something I was passionate about.
Earthforce was one of the reasons I joined Salesforce.
Lindsey Peterson, Global President of Earthforce, Salesforce’s Equality Group
Naturally, when I joined Salesforce, I got involved in Earthforce right away. I started by co-leading the Earthforce hub in Sydney, and I approached the global leadership team about additional ways to get more involved. There was an open role for the Global Growth Chair position within Earthforce, and after a year and a half, I stepped into the Global President’s role, where I’ve been for the last three years.
Our vision is to create a better planet for all people by being multipliers for sustainable and equitable change. Earthforce is an educational space where we have conversations to learn more about climate action, sustainability, waste management, and how to drive impact.
We’re also focused on creating opportunities for volunteerism, specifically around restoration projects that will have lasting results on the community and planet. For example, we’ve organized litter pickups, dune restoration projects, tree planting, and generative bush care in places like Sydney. During my time as Global President, we’ve achieved more than 280,000 employee volunteer hours in our communities around the world.
One example is our partnership with the Real Estate and Workplace Services (REWS) team to help influence waste management in our buildings. We’ve partnered with REWS to understand our leasing structures and where waste goes in our buildings, influence more sustainable practices, and educate employees on how to manage their waste effectively.
For example, the blackwater system in Salesforce Tower in San Francisco is a first-of-its-kind green technology that recycles the building’s wastewater, saving an estimated 30,000 gallons of water per work day. And Salesforce Tower Sydney, where I’m based, is also one of the most sustainable office buildings in Sydney.
To kick off Earth Month, we hosted an educational session on the environmental impact of AI and Salesforce’s sustainable approach to AI. Throughout the month, we’ll activate our global members through opportunities to give back to our communities. We’re organizing tree-planting efforts in major cities like Chicago, Atlanta, and New York. Globally, employees can volunteer to map the Amazon Rainforest. Through this effort, volunteers will incorporate Indigenous and local community knowledge around settlements, water sources, and sacred sites into a comprehensive map of the Amazon, providing more holistic information to conservation and restoration teams on the ground.
Global Earthforce President Lindsey Peterson attends Salesforce’s annual Global Equality Leadership Summit (GELS) and participates in a monthly Earthforce volunteer event with Defy Design, an innovator in the waste and plastic space.
Like all Equality Groups, we want to use employee voices to create positive change. We need to take climate action now, and it can be challenging to know where to start to feel you are making a true impact.
We surveyed our members and one of their top asks was for climate education. At the end of the month, we’re launching a sustainability storytellers program, which will empower our members to be able to talk about Salesforce’s sustainability journey, Net Zero Cloud, emissions reductions, and more. We want to educate people on this landscape so they can bring their knowledge and passion to their day job.
Everyone is a multiplier for change, and when we come together, we can amplify the impact of our actions. This means not only adopting sustainable practices individually, but also advocating for systemic changes, influencing policy, and mobilizing others to take action. While small-scale initiatives are important, it will take large, global policy shifts — beyond the scope of what individuals can do in our everyday lives — to make lasting change.
While small-scale initiatives are important, it will take large, global policy shifts — beyond the scope of what individuals can do in our everyday lives — to make lasting change.
Lindsey Peterson, Global President of Earthforce, Salesforce’s Equality Group
I love challenging our members to elevate their understanding of what sustainability means and helping them uncover the many ways to drive climate action. I am deeply grateful for the opportunity to bring my passion for people and the planet to work every day.
In a recent Salesforce survey, a striking 60% of public sector IT professionals identified a shortage of artificial intelligence (AI) skills as their top challenge to implementing AI.
Why it matters: AI could save hundreds of millions of government staff hours and billions of dollars annually, according to Deloitte. The benefits of AI are only possible if the public sector workforce has the skills to harness the technology. Government agencies are already being directed to implement guidelines and build teams to support the use of AI. This includes expanding and upskilling their AI talent and designating a new Chief AI Officer, which every federal agency was recently ordered to hire.
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Salesforce perspective: “Training and skills development are critical first steps for the public sector to leverage the benefits of AI. By investing in new skills like prompt development, public sector leaders can empower their workforce to use AI to increase productivity, build deeper relationships with constituents, and improve the quality of public services.” – Casey Coleman, SVP, Global Government Solutions
By investing in new skills like prompt development, public sector leaders can empower their workforce to use AI to increase productivity, build deeper relationships with constituents, and improve the quality of public services.
Casey Coleman, SVP, Global Government Solutions
IT professionals in the public sector are about a third more likely to say there’s an AI skills gap in their organization, compared to the industry* average.
By bridging the AI skills gap, organizations can create new efficiencies in the public sector. Salesforce’s survey shows that the public sector’s main goal with AI is to automate routine tasks.
*Methodology: In partnership with Vanson Bourne, Salesforce conducted a double-anonymous survey of 600 IT professionals (200 IT leaders and 400 IT individual contributors) in Australia, France, Germany, the United Kingdom, and the United States. Respondents work across industries, including technology, financial services, media and entertainment, manufacturing, retail, healthcare, the public sector, and more. The survey was fielded in December 2023 and January 2024.
New Caseworker Narrative Generation helps government employees work cases faster by automating manual tasks with AI
Salesforce now offers several FedRAMP-compliant features for products like Field Service, Privacy Center, Security Center, and GovSlack
Salesforce today announced Public Sector Einstein 1 for Service, including CRM, trusted AI, and data capabilities to help government employees automate administrative tasks and provide faster service to constituents. Built on the Einstein 1 platform, public sector organizations can now quickly and easily generate case reports, capture real-time call transcriptions, and document and format case interactions, all in a single offering.
Why it matters: BCG estimates that generative AI could unlock a $1.75 trillion productivity opportunity annually across many functions and levels of government. However, 62% of IT decision makers across industries, including those in the public sector, feel their organization’s data systems are not ready to leverage AI.
Innovation in action: Public Sector Einstein 1 for Service offers government contact center agents and case managers trusted conversational and generative AI, enabling them to be more productive and efficient. Features include:
High-quality AI requires high-quality data and insights: Public Sector Einstein 1 for Service also includes Data Cloud, which connects and harmonizes data and uses it to power government agency applications.
What’s new in compliance: Salesforce also now offers several Federal Risk and Authorization Management Program (FedRAMP) compliant tools to help government agencies drive efficiency and productivity while meeting regulatory requirements. These tools include:
With Public Sector Einstein 1 for Service, organizations can implement trusted AI to become more efficient, better manage and harmonize their data, and give employees the tools they need to better serve their constituents, all while driving their mission forward.
Nasi Jazayeri, EVP & GM, Public Sector
Salesforce perspective: “Public sector organizations want to simplify their technology stack, better engage with constituents, and reduce employees’ administrative burdens while improving employee productivity. With Public Sector Einstein 1 for Service, organizations can implement trusted AI to become more efficient, better manage and harmonize their data, and give employees the tools they need to better serve their constituents, all while driving their mission forward.” – Nasi Jazayeri, EVP & GM, Public Sector
Any unreleased services or features referenced here are not currently available and may not be delivered on time or at all. Customers should make their purchase decisions based upon features that are currently available.
