Salesforce touts trust and security features when introducing its new AI Cloud, but it doesn't differ much from existing offerings, and analysts believe there may be few takers for AI Cloud's expensive starter package.
Zasluge: Magdalena Petrova
Salesforce's new AI Cloud has left many wondering what it's all about: how it differs from the competition, what's new on offer, and whether you should consider subscribing. Analysts predict there may be only a few interested in the expensive new offering.
Salesforce AI Cloud kombinira Slack GPT, Tableau GPT,top of the GPT, MuleSoft GPT, Flow GPT, Service GPT, Marketing GPT and Commerce GPT along with the new Einstein Trust layer and rapid engineering training toollarge language models (LLM)).
A new integrated offer, which focuses ongenerative AIapps, according to CEO Marc Benioff, build on the unification of Salesforce's existing technology stack already offered through products includingGPT Einstein,data cloud,Graph,Flowgsoft mule.
Syn unified interface for AI Cloud
Although Salesforce promotes AI Cloud as an integrated offering through the Cloud Starter Pack, which costs $360,000 annually and includes a free AI readiness assessment for Salesforce Professional Services, it does not have a single, unified interface, the company said.
"Much of cloud AI will actually manifest as assistants in the various cloud offerings that we have, for example, Sales GPT in Sales Cloud, Marketing GPT in Marketing Cloud and Service GPT in Service Cloud," said Jayesh Govindarajan. senior vice president. president of data science and engineering at Salesforce.
"However, if you're an independent service provider and want to build your own queries, AI Cloud will offer a separate local console with a low-code experience for training large language models," Govindarajan said, adding that Salesforce has already signed up. with service partners including Accenture, Deloitte and PwC.
The AI Cloud Starter Pack, according to Forrester's principal analyst Liz Herbert, is only a pricing model for the products the company promotes, and "not many Salesforce customers will use that model or be forced to buy it," since most companies already have a CRM. and other installed software packages.
"If you look at how the typical customer has already signed up for Salesforce, it's highly unlikely that bundling is a common way that someone would shop," Herbert said, adding that Salesforce also hasn't been very specific about the pricing elements for businesses to use. only one or more offers in AI Cloud. The pricing structure is expected to align over time with the use of different offerings under AI Cloud, Herbert said.
Salesforce AI Cloud offers a selection of LLMs
Salesforce's AI Cloud architecture is built to support multiple LLMs and their training, according to the company.
AI Cloud architecture is compatible with business public cloud infrastructure architecture,hypersila, which in turn supports a data cloud layer, followed by a layer that hosts multiple LLMs (proprietary or third-party), topped by a new Einstein trust layer, the company said.
The trust layer separates Einstein's GPT-based generative AI engines such aslazy GPT,Table GPT, GPT Marketing i GPT Commerce– rapid engineering tools and prediction engines, Salesforce said.
The LLMs AI Cloud currently offers include third-party models from Amazon Web Services (AWS), Anthropic, and Cohere, among others.
Salesforce will also provide its own LLMs such as CodeGen, COdeT5+, and CodeTF to implement generative artificial intelligence in applications, especially those that aim to increase productivity, reduce the talent gap, and reduce technology implementation costs.
A new division, the so-calledSalesforce AI Research, was created to try to develop new applications for AI by advancing new LLMs or developing existing ones.
Companies, according to Salesforce, can also train their LLMs on their own domain-specific data.
"These models, either passing throughAmazon SageMakeroGoogle Vertex AI, will connect directly to the AI Cloud via the Einstein GPT Trust Layer. In this scenario, customer data can remain within user trust boundaries," the company said.
How do multiple LLMs work together?
Contrary to the practices of some large software vendors who claim to mix different LLMs to offer generative AI applications, Salesforce's AI Cloud "selects the right LLM for the right task," according to the company.
"Determining the right LLM is based on the results the system has previously seen," Govindarajan said, adding that the LLM recommendation engine learns from data across all Salesforce deployments.
Giving the example of Marketing GPT creating a landing page, Govindarajan said the system tracks the performance of that landing page, as performance data is also stored within Salesforce's Marketing Cloud.
"If the landing page worked really well, it will suggest the same LLM you used to create the landing page to another user who also wants to create a similar landing page," Govindarajan said.
The same logic also applies to the multiple flavors of Einstein GPT across Salesforce Cloud offerings that continuously empower participants, Salesforce said.
“These generative AI helpers, like Slack GPT or Tableau GPT, track whether the user ends up following a suggestion. It also tracks any edits or changes to the generated output. This helps it to continuously learn and be more personalized for users,” said Govindarajan.
Einstein uses the GPT Trust Layer NOW
Salesforce's Einstein GPT Trust layer isn't new or special, according to Forrester's Herbert, who says it follows the same principles most other vendors offer in terms of security. Like most other service providers, Salesforce usesidentity and access management (IAM)rights in the company to protect privacy and data security, said Salesforce's Govindarajan.
"After a user runs a query on their system, the technology stack behind these generative AI helpers searches the databases for the attribute they need and have access to, and then the stack builds a semantic search model based on the company-wide knowledge graph and the searching employee query,” said Govindarajan.
“The retrieved vectorized data is stored within the company's servers, masked, and then fed into a large language model to generate results or responses. So the stack essentially copies or absorbs identity and access management policies that already exist for that employee,” Govindarajan added.
The architecture of the Einstein Trust layer is also built in such a way that after processing the query, the information contained in the notification or query is not retained, the company said, adding that the generated output is checked for toxicity. and audit trail. records are kept for all indications.
The offerings under AI Cloud, according to the company, will be available in different phases, with Einstein GPT and Service GPT becoming generally available in June.
The company's commercial GPT will be generally available in July. Other offers within the bundle are expected to be available next year after being in pilot for most of 2023.
It will be interesting to see how customers react to Salesforce's new offering, which is more of an amalgamation of existing offerings than an entirely new platform. However, analysts believe that the Salesforce AI Cloud will help increase confidence in the use of generative artificial intelligence by companies.
“Salesforce recognizes that there are barriers to adoption of artificial intelligence, especially trust. Therefore, they double this aspect. Another challenge is that we will soon have a large number of LLMs: open source, public and private, which will lead to confusion about which one to implement. So Salesforce AI Cloud enables users to connect LLMs of their choice,” said Sanjeev Mohan, principal analyst at SanjMo.
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