Large language models or LLMs are a cutting-edge form of artificial intelligence that have gained significant attention in recent years. These models are designed to understand and generate human language, making them incredibly powerful tools for a wide range of applications.
At their core, large language models like GPT 4 are trained on vast amounts of text data, such as books, articles, and websites. This training allows the model to learn the rules and patterns of language, enabling it to generate coherent and contextually appropriate responses.
Before we take a look at some of the best LLMs, there is a term that you may come across frequently called ”parameters”. So, what are they?
Parameters simply refer to variables that are modified during the training phase in order to determine how input data is converted into the desired output. These individual parameters correspond to values that are obtained and adjusted by an AI algorithm throughout the training process.
This enables it to make informed decisions and predictions. The values of these parameters have a significant impact on the performance of a model and influence factors such as accuracy, speed, and generalization capabilities.
LLMs have revolutionized the field of natural language processing (NLP) and artificial intelligence (AI). With how competitive this field is, there have already been quite a lot of LLMs. But there are a handful that stand out.
This is the forefront of AI large language models in 2023. Developed by OpenAI and unveiled in March, this remarkable model showcases a range of astonishing capabilities. It has a profound understanding of complex reasoning, advanced coding abilities, exceptional performance in various academic evaluations, and numerous other competencies that mirror human-level proficiency.
GPT-4 also incorporates multimodal capability. This enables it to process both text and image inputs. While ChatGPT has yet to inherit this feature, fortunate users have experienced it through Bing Chat, which harnesses the power of the GPT-4 model.
GPT-3.5 is a versatile LLM. it excels in speed, providing complete responses within seconds. Whether it's crafting essays using ChatGPT or developing business plans, GPT-3.5 performs admirably.
Additionally, OpenAI has expanded the context length to a generous 16K for the GPT-3.5-turbo model, further enhancing its appeal. This model can also be used freely without any hourly or daily limitations.
This large language model by Google has emerged as a standout among the leading large language models of 2023. What sets this model apart is its strong focus on vital areas such as commonsense reasoning, formal logic, mathematics, and advanced coding across over 20 languages.
The most comprehensive version of PaLM 2 has been trained with an astounding 540 billion parameters and boasts an impressive maximum context length of 4096 tokens. PaLM 2 comprises four different models within its framework: Gecko, Otter, Bison, and Unicorn.
Currently only Bison is accessible to users. In terms of performance evaluation based on the MT-Bench test, Bison achieved a score of 6.40 and falls slightly behind GPT-4's remarkable score of 8.99 points.
In 2023, Anthropic, a company founded by former employees of OpenAI and backed by Google, launched Claude v1, an impressive competitor in the realm of large language models. Anthropic's primary goal is to develop AI assistants endowed with qualities such as helpfulness, honesty, and harmlessness.
The remarkable performance of both the Claude v1 and Claude Instant models has been evident in various benchmark tests, surpassing PaLM 2 in both the MMLU and MT-Bench evaluations. It achieves a score of 7.90 in the MT-Bench test, while GPT-4 attains 8.99. In the MMLU benchmark, Claude v1 secured 75.6 points, slightly trailing behind GPT-4's score of 86.4.
These scores provide insights into model performance and help drive advancements in natural language processing.
FLAN-UL2 is a reliable and scalable model that excels in various tasks and datasets. It is based on the T5 architecture and has improvements compared to the UL2 model. With an extended receptive field of 2048, it simplifies inference and fine-tuning, making it good for in-context learning. FLAN datasets and methods are openly accessible for effective instruction tuning.
Codex is a derivative of GPT-3 and exhibits exceptional proficiency in programming, writing, and data analysis. Developed in collaboration with GitHub and GitHub Copilot, it showcases its ability to comprehend and execute natural language commands for various programming languages.
GPT-NeoX-20B exhibits remarkable capability in a broad spectrum of natural language processing tasks. Functioning as a dense autoregressive language model with 20 billion parameters, it distinguishes itself among other models in its category.
Trained on the Pile dataset, GPT-NeoX-20B currently holds the record for being the largest autoregressive model with publicly available weights. Its versatility makes it exceptional while performing tasks related to language understanding, mathematics, and knowledge-based domains.
Jurassic-2 comprises three primary language models: Large, Grande, and Jumbo. These models exhibit advanced proficiency in reading and writing tasks. Recently, they have acquired the ability to understand and execute natural language instructions without the need for specific examples, owing to their instruction capabilities.
These models also have showcased exceptional performance on Stanford's Holistic Evaluation of Language Models (HELM), a renowned benchmark for evaluating language models.
One notable feature of WizardLM is its capability to rephrase initial instructions into more complex ones. The resulting instruction data is then utilized to fine-tune the LLaMA model, thereby enhancing its performance.
Deepmind's creation, the Gopher, is an awe-inspiring model encompassing 280 billion parameters. It showcases remarkable proficiency in understanding and generating language, while demonstrating exceptional aptitude across diverse domains such as mathematics, science, technology, humanities, and medicine.
Moreover, it also possesses the unique capability to simplify complex subjects during interactive conversations. With its expertise in reading, fact checking and identification of harmful language, Gopher undoubtedly proves to be an invaluable asset.
These were just some of the few of the hundreds of LLMs that are currently out there. As you may have noticed, that's already quite a few, each distinct in its own way. This is just the beginning of a new dawn where AI will truly be the future of mankind.
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