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OpenAI
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Google Launches Next-Gen Large Language Model, PaLM 2

Google has launched its latest large language model, PaLM 2, in a bid to regain its position as a leader in artificial intelligence. PaLM 2 is an advanced language model that can understand the nuances of human language and generate responses that are both accurate and natural-sounding.

The new model is based on a transformer architecture, which is a type of deep learning neural network that excels at understanding the relationships between words and phrases in a language. PaLM 2 is trained on a massive dataset of language, which enables it to learn from a diverse range of sources and improve its accuracy and comprehension over time.

PaLM 2 has several features that set it apart from previous language models. One of these is its ability to learn from multiple sources simultaneously, which allows it to understand a broader range of language than previous models. It can also generate more diverse and natural-sounding responses, making it ideal for applications such as chatbots and virtual assistants.

Google has already begun using PaLM 2 in its products and services, such as Google Search and Google Assistant. The model has also been made available to developers through Google Cloud AI, allowing them to build more advanced applications and services that can understand and respond to human language more accurately.

The launch of PaLM 2 is significant for Google, as it comes at a time when the company is facing increased competition from other tech giants such as Microsoft and OpenAI. Both of these companies have recently launched large language models of their own, which are also based on transformer architectures.

Google hopes that PaLM 2 will help it to regain its position as a leader in AI research and development. The company has invested heavily in machine learning and natural language processing over the years, and PaLM 2 is a testament to its ongoing commitment to these fields.

In conclusion, Google's PaLM 2 is an advanced language model that has the potential to revolutionize the way we interact with technology. Its ability to understand and respond to human language more accurately and naturally is a significant step forward in the development of AI, and it will be exciting to see how developers and businesses leverage this technology to build more advanced applications and services.


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Technology
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Meta Announces a New AI-powered Large Language Model


On Friday, Meta introduced its new AI-powered large language model (LLM) named LLaMA-13B that, in spite of being "10x smaller," can outperform OpenAI's GPT-3 model. Language assistants in the ChatGPT style could be run locally on devices like computers and smartphones, thanks to smaller AI models. It is a part of the brand-new group of language models known as "Large Language Model Meta AI," or LLAMA. 

The size of the language models in the LLaMA collection ranges from 7 billion to 65 billion parameters. In contrast, the GPT-3 model from OpenAI, which served as the basis for ChatGPT, has 175 billion parameters. 

Meta can potentially release its LLaMA model and its weights available as open source, since it has trained models through the openly available datasets like Common Crawl, Wkipedia, and C4. Thus, marking a breakthrough in a field where Big Tech competitors in the AI race have traditionally kept their most potent AI technology to themselves.   

In regards to the same, Project member Guillaume’s tweet read "Unlike Chinchilla, PaLM, or GPT-3, we only use datasets publicly available, making our work compatible with open-sourcing and reproducible, while most existing models rely on data which is either not publicly available or undocumented." 

Meta refers to its LLaMA models as "foundational models," which indicates that the company intends for the models to serve as the basis for future, more sophisticated AI models built off the technology, the same way OpenAI constructed ChatGPT on the base of GPT-3. The company anticipates using LLaMA to further applications like "question answering, natural language understanding or reading comprehension, understanding capabilities and limitations of present language models" and to aid in natural language research. 

While the top-of-the-line LLaMA model (LLaMA-65B, with 65 billion parameters) competes head-to-head with comparable products from rival AI labs DeepMind, Google, and OpenAI, arguably the most intriguing development comes from the LLaMA-13B model, which, as previously mentioned, can reportedly outperform GPT-3 while running on a single GPU when measured across eight common "common sense reasoning" benchmarks like BoolQ, PIQA LLaMA-13B opens the door for ChatGPT-like performance on consumer-level hardware in the near future, unlike the data center requirements for GPT-3 derivatives. 

In AI, parameter size is significant. A parameter is a variable that a machine-learning model employs in order to generate hypotheses or categorize data as input. The size of a language model's parameter set significantly affects how well it performs, with larger models typically able to handle more challenging tasks and generate output that is more coherent. However, more parameters take up more room and use more computing resources to function. A model is significantly more efficient if it can provide the same outcomes as another model with fewer parameters. 

"I'm now thinking that we will be running language models with a sizable portion of the capabilities of ChatGPT on our own (top of the range) mobile phones and laptops within a year or two," according to Simon Willison, an independent AI researcher in an Mastodon thread analyzing and monitoring the impact of Meta’s new AI models. 

Currently, a simplified version of LLaMA is being made available on GitHub. The whole code and weights (the "learned" training data in a neural network) can be obtained by filling out a form provided by Meta. A wider release of the model and weights has not yet been announced by Meta.  

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