IBM Presents Granite 3.0 AI Models For Commercial Applications.

(VOR News) – IBM made the announcement that it has published its most recent suite of artificial intelligence (AI) models, which is named Granite 3.0, during the annual TechXchange event that takes place in Las Vegas. The event is held annually.

According to IBM, the third-generation models, which are a part of the Granite flagship line, are designed to contain performance levels that are equivalent to those of comparable-sized models supplied by other vendors.

These models from IBM are also expected to be extremely affordable.

It has been said by Big Blue that these models have been reviewed based on a wide range of academic and industry criteria, with a special emphasis placed on performance, transparency, and safety.

Granite models are made accessible to the public under the Apache 2.0 license, which is in agreement with the open-source artificial intelligence technique that IBM employs.

This license gives enterprise customers and the community the flexibility and autonomy to implement the models in accordance with their own requirements, which empowers them to make decisions quickly and easily.

The Granite 3.0 series includes models that are a blend of experts, models that are focused on safety, and models that are general-purpose language models. All of these models are included in the series.

The retrieval-augmented generation (RAG) process, categorization, summarization, and entity extraction are some of the activities that these models are developed for. They also have the capability of being fine-tuned by making use of data that is specific to the firm, which makes it easier for them to be incorporated into a number of processes that are carried out inside an organization.

In addition, the most recent models of artificial intelligence that have been developed by IBM have built-in safety protocols that provide risk assessments of user prompts and responses. Furthermore, the models are able to identify potential hazards, such as potentially harmful information and instances of social bias that may be present.

Additionally, they carry out checks that are specifically tailored to RAG use circumstances, which ensures that the information is correct and pertinent to the context in which it is being used.

In addition, Big Blue has presented models that are a combination of experts. As a result of the fact that these models are designed to be implemented in low-latency contexts, they are suitable for setups that are based on information technology and the edge.

The enterprise data is supported by these models, which also comprise smaller Granite models. These models are built by utilizing the alignment approach known as InstructLab, which was developed in partnership with Red Hat. IBM states that early proofs of concept reveal cost reductions that range from three to twenty-three times those of larger models.

Compared to larger models, IBM’s reductions are significant.

In addition to platforms such as HuggingFace, IBM’s Watsonx, and NVIDIA NIM microservices, the Granite 3.0 models can also be accessed through additional cloud services such as Google Cloud’s Vertex AI Model Garden, Ollama, and Replicate.

These cloud services are also examples of additional cloud infrastructures.

Additionally, the strategic agreements that IBM has created with providers such as Amazon Web Services (AWS), Salesforce, and SAP offer greater integration choices for enterprise users. These agreements involve the formation of strategic partnerships.

The artificial intelligence (AI) latency that IBM provides is a source of concern for the industry.

Despite the fact that IBM has achieved substantial advancements in artificial intelligence technology, including the development of platforms such as Watsonx, the company has been subjected to criticism for falling behind competitors such as Microsoft and Google in terms of monetisation and efficacy.

This criticism has been levelled against IBM. Moreover, there are individuals within the organization who have expressed disagreement with the company’s goals of replacing 7,800 positions with artificial intelligence, stating that these goals are not practical.

In December 2023, CNBC had an interview with Arvind Krishna, the CEO of IBM. During the course of the discussion, Krishna revealed that the company had been hesitant to capitalize on its successes in artificial intelligence.

Krishna explained that the approach that the company used consisted of the development of large and complex solutions, which he acknowledged were not suitable for market adoption at the time. He claimed that this was the technique that the corporation had taken.

SOURCE: TMN

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