Command R and Command R+ received an upgrade on essentially all tasks. They are now better at recall, speed, math, and reasoning.

OpenAI has released two new "chain-of-thought" models, o1-preview and o1-mini, which prioritize reasoning over speed and cost. These models are trained to think step-by-step, enabling them to handle more complex prompts requiring backtracking and deeper analysis. While the reasoning process is hidden from users due to safety and competitive advantage concerns, it allows for improved results in tasks like generating Bash scripts, solving crossword puzzles, and validating data.

xAI announced its next model, with 128k context length and improved reasoning capabilities. It excels at retrieval and programming.

OpenAI has recently introduced a new series of models known as the o1 models, which have garnered attention for their impressive reasoning capabilities. These models, particularly o1-preview and o1-mini, represent a significant advancement in artificial intelligence, especially in solving complex problems that previous models struggled with. The o1 models are built on a foundation of reinforcement learning, which enhances their ability to reason and solve problems in a more structured and effective manner. The development of these models follows the earlier Q* project, which aimed to tackle challenging mathematical problems. The project was later renamed Strawberry, and the unveiling of the o1 models marks a pivotal moment in OpenAI's research. The o1 models have demonstrated exceptional performance in various reasoning tasks, outperforming other leading models in the market. They have successfully solved intricate text-based puzzles and mathematical problems, showcasing a leap in reasoning capabilities compared to earlier iterations like GPT-4. A key aspect of the o1 models' success lies in their training methodology. Unlike traditional models that rely heavily on imitation learning, which can lead to compounding errors, the o1 models utilize reinforcement learning. This approach allows them to learn from a broader range of problem-solving scenarios, enabling them to break down complex tasks into manageable steps. For instance, when faced with a programming challenge, the o1 model can dissect the problem into smaller components, systematically addressing each part to arrive at a solution. Despite their advancements, the o1 models are not without limitations. They still struggle with certain types of reasoning, particularly spatial reasoning and tasks that require a nuanced understanding of two-dimensional spaces. For example, when presented with navigation problems or chess scenarios, the o1 models have shown a tendency to provide incorrect or nonsensical answers. This highlights a gap in their ability to process and analyze information in a way that mimics human cognitive skills. Moreover, while the o1 models excel in structured reasoning tasks, they face challenges in real-world applications where context and accumulated knowledge play crucial roles. Human cognition often involves synthesizing information from various sources and retaining key concepts, a capability that current AI models, including o1, have yet to fully replicate. The context window limitations of these models further constrain their ability to handle complex, multifaceted problems that require extensive background knowledge. In summary, OpenAI's o1 models represent a significant step forward in AI reasoning capabilities, particularly in mathematical and programming contexts. Their reliance on reinforcement learning has allowed them to achieve remarkable performance in structured tasks. However, challenges remain in areas such as spatial reasoning and real-world problem-solving, indicating that while these models are powerful, they are still a long way from achieving human-level intelligence.

OpenAI has released its next model, which was trained to think before it answers. The new model was trained with reasoning traces and spends time considering before it answers. In some domains, this has led to super human performance. The model will be rate limited to 30 or so queries per user per week, but OpenAI hopes to lift that restriction soon.

OpenAI is reviving its robotics research group after a three-year hiatus, aiming to develop multimodal robotics models and improve core AI models.

OpenAI o1 is a new large language model trained to reason by generating a chain of thought before responding. This model demonstrates significant advancements in reasoning capabilities, achieving impressive performance in various tasks, including competitive programming, math Olympiads, and scientific problem-solving. OpenAI o1-preview is now available for use in ChatGPT and through the API, allowing users to explore its reasoning abilities.

Command R fine-tuning offers industry-leading performance at a fraction of the cost. Command R with fine-tuning consistently outperforms larger models across key performance metrics that matter most for businesses. Command R fine-tuning is immediately available for businesses and developers on Cohere's platform and Amazon Sagemaker.

Google is intensifying its competition with OpenAI by developing advanced artificial intelligence models that possess reasoning capabilities. Recent reports indicate that teams at Google have made significant strides in creating software that mimics human-like reasoning, particularly in solving multistep problems. This development is part of Google's broader focus on enhancing the reasoning abilities of large language models (LLMs), which includes techniques like chain-of-thought prompting. Chain-of-thought prompting allows LLMs to tackle complex inquiries by breaking them down into a series of intermediate reasoning steps, akin to human thought processes. This method results in longer response times, as the models analyze similar prompts before formulating a comprehensive answer. The ability to engage in such reasoning enables these models to handle intricate tasks related to mathematics and computer programming more effectively. OpenAI is also employing chain-of-thought prompting in its latest model, known internally as Strawberry, which was released in September. Initially, there were concerns within Google's DeepMind unit about falling behind OpenAI, but these worries have diminished as Google has introduced more competitive products. OpenAI's new model, however, lacks some features present in the current version of ChatGPT, such as web browsing and file uploads, which are considered useful. In addition to its work on reasoning capabilities, Google is enhancing its Gemini chatbot. The company recently launched its 1.5 Flash model, which is designed to provide faster and more efficient responses. This update aims to improve Gemini's reasoning and image processing skills, promising users a more effective interaction experience. Overall, Google's advancements in AI reasoning reflect its commitment to staying competitive in the rapidly evolving landscape of artificial intelligence, particularly against the backdrop of OpenAI's innovations.

Cohere For AI has created a 30B+ parameter model that is quite adept at reasoning, summarization, and question answering in 10 languages.

This guide was missed in the excitement of OpenAI's new reasoning models. It shows how prompting this new model is different and requires simpler prompts and a more structured input context.

OpenAI has released o1 and o1-mini, the first in a series of reasoning models that have been trained to answer more complex questions faster than a human can. The model is better at writing code and solving multistep problems than previous models, but it is more expensive for developers and slower to use than GPT-4o. The release is still in preview to indicate how nascent it is. ChatGPT Plus and Team users should already have access to the model, while Enterprise and Edu users will get access early next week. OpenAI plans to bring o1-mini access to all free users, but it hasn't set a release date yet.

Meta has released an 8B and 70B model with dramatically improved performance, particularly in reasoning, context length, and code. It is still training a 400B parameter model, which will match Opus in performance. These models are easily the most powerful available open models.

Cohere has introduced Command R+, a powerful, scalable LLM designed for enterprise use cases, featuring advanced retrieval augmented generation with citation, multilingual coverage in 10 key languages, and tool use capabilities.

Cohere’s newly launched RAG-optimized Command-R model, designed for businesses to get into large-scale production, is coming to the recently launched NVIDIA API catalog.

OpenAI has announced new enterprise-grade features for its API customers, including enhanced security measures, an upgraded Assistants API, a new Projects feature for granular access control, and cost management tools. These updates demonstrate OpenAI's focus on offering a more "plug and play" experience for enterprises, countering the rise of competitors like Meta's Llama 3 and open models from Mistral.

OpenAI published research on giving system prompts stronger weighting, which dramatically improves model robustness to jailbreaks and adversarial attacks.

xAI has announced that its latest flagship model has vision capabilities on par with (and in some cases exceeding) state-of-the-art models.

OpenAI and Google have introduced advanced AI models that enable real-time multimodal understanding and responses and promise improved AI assistants and innovations in voice agents. OpenAI's GPT-4o boasts double the speed and half the cost of its predecessor, while Google's Gemini 1.5 Flash delivers a significant reduction in latency and cost. Both tech giants are integrating AI across their ecosystems, with OpenAI eyeing consumer markets, which could potentially reach up to a billion users, with its products and partnerships.

Elon Musk's xAI has released Grok-1.5, an AI with enhanced math and coding skills that boasts a significant performance increase and competitive benchmark results against leading AI models like GPT-4. The updated model can now process much longer context windows, improving its memory capacity. Grok-1.5 is currently accessible to Premium+ users of X. X plans to expand availability to regular Premium subscribers.

OpenAI has released a set of code for its rules based rewards for language model safety project. It includes some data they used for training.

Covariant has introduced RFM-1, aiming to revolutionize robotics with a large language model for robot language that enhances robots' decision-making and interaction capabilities across various industries by utilizing a massive data collection from its Brain AI platform.

Covariant has introduced RFM-1, aiming to revolutionize robotics with a large language model for robot language that enhances robots' decision-making and interaction capabilities across various industries by utilizing a massive data collection from its Brain AI platform.

OpenAI and Meta are teasing the next iterations of their AI models, expected to feature enhanced reasoning and planning capabilities. Dubbed GPT-5 and Llama 3, the models aim to advance toward artificial general intelligence, with vague release timelines and application details. The tech community remains skeptical given the history of overhyped AI promises with limited substantive evidence.

xAI has released its newest model, Grok 2, a frontier class model capable of reasoning, code, and mathematics. It is collaborating with Black Forest Labs to bring FLUX to X users.

Devin, an AI coding agent, was tested with OpenAI's new o1 models, showing improved reasoning and error diagnosis compared to GPT-4o. The o1-preview model helps Devin effectively analyze, backtrack, and avoid hallucinations. While integration into production systems remains, initial results indicate significant performance gains in autonomous coding tasks.

OpenAI is testing out a prototype search system.

Large language models sometimes fail at tasks like counting letters due to their tokenization methods. This highlights limitations in LLM architecture that affect their understanding of text. Nevertheless, advancements continue, such as OpenAI's Strawberry for improved reasoning and Google DeepMind's AlphaGeometry 2 for formal math.

Answer AI has released a new FSDP/QLoRA training tool that makes it possible to train 70B parameter models on consumer GPUs. It has open sourced the code and made it easy to run locally or on runpod.

OpenAI and Anthropic have agreed to allow the US government early access to their major new AI models before public release to enhance safety evaluations as part of a memorandum with the US AI Safety Institute.