The unfolding of an AI-driven economy over the past 18 months will redefine industries and revolutionise how humans live and work – and large language models (LLM) will be key.
So who’s winning in this burgeoning LLM space? Data analytics and consulting company GlobalData ranks the main players.
Generative AI (GenAI) platforms are largely based on multimodal foundation models and LLM; these are borne out of growing interest in accessing natural language processing (NLP) to query computers, following the significant advancements in AI seen in recent years. These include machine learning and deep learning via neural networks, also called generative adversarial networks (GANs), and finally the emergence of the ‘transformer’ architecture in 2017, representing breakthrough efficiencies in training models.
The emergence of LLM
The phenomenon of GenAI builds on the precursor of new software architectures, hybrid cloud, automation, and advancements in AI, resulting in the emergence of LLMs. LLMs are deep learning models trained using vast amounts of text.
They are designed to produce new levels of content creation, automation of repetitive tasks, and deliver personalisation for improving the customer experience, and their performance depends on the quality and size of the pretraining dataset.
“The term LLM was largely unheard of before the end of 2022, which makes its explosive growth and mega investments both startling and somewhat overwhelming. Its immaturity also makes evaluating competitors’ closely guarded training methodologies challenging,” says Research Director Charlotte Dunlap, Enterprise Technology and Services at GlobalData. GlobalData, therefore, has just released its newest Competitive Landscape Assessment report analysing and rating eight LLM competitors.
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By GlobalDataGlobalData Competitive Landscape Assessment
The new GlobalData report evaluates the competitors’ differentiators of core model technology including context windows, multimodal and multilingual capabilities, vertical and horizontal use cases, AI guardrails, ecosystem, professional services, and go-to-market strategies.
Google has been named ‘Leader’ by GlobalData due to a combination of highly developed model capabilities in the Google Gemini family and sophisticated enterprise tooling to build and scale GenAI applications. OpenAI is ‘Very Strong’ thanks to its core model technology with solid code generation and multilingual capabilities, multimodality, and context window size.
Microsoft is also rated ‘Very Strong’ for its high degree of penetration in the enterprise and tooling anchored in the powerful capabilities of its exclusive GenAI partner, OpenAI, and for Microsoft’s proprietary model, Phi.
IBM is also rated in the ‘Very Strong’ category for its strengths in generating computer code, along with a broad range of native language support, and third-party model support. Amazon, Anthropic, and Meta have been ranked ‘Strong,’ and Cohere is ranked ‘Competitive.’
The right LLM choice
“Choosing the right large language model can be a challenging task for enterprises. The GenAI market is notoriously difficult to evaluate and the constant media coverage of improvements in model size, context windows, or performance benchmarks, often only adds to the confusion,” says Senior Analyst Beatriz Valle, Enterprise Technology and Services at GlobalData.
“Enterprise buyers must also look at other indicators, for example, whether a vendor has a clear strategy with practical use cases that drive a solid ROI (return on investment) on business applications. What are the solutions in the generative AI market that are going to make a substantial difference in driving profitability and efficiencies?”
Following OpenAI’s release of ChatGPT, major cloud and platform providers, hardware/chip manufacturers, and startups moved quickly, recognising the potential of a revolutionary technology unparalleled since the birth of the internet.
Over the past 18 months, these vendors have leveraged their previous AI development efforts and set out building and training models as part of a GenAI portfolio to help address customers’ business transformations.
