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AI Shorts

Arcee AI unveils the revolutionary Arcee Agent: A state-of-the-art language model with 7 billion parameters. This model is uniquely designed for performing function calls and utilizing tools.

Arcee AI, a leading artificial intelligence (AI) company, has launched Arcee Agent, a novel 7 billion parameter language model designed for function calling and tool usage. The model is smaller in size compared to its contemporaries, a difference which does not compromise performance but significantly cuts the computation needs. Developed using the high-performing Qwen2-7B architecture…

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Researchers at DeepSeek AI have suggested implementing Expert-Specialized Fine-Tuning (ESFT) as a way to cut down memory usage by as much as 90% and reduce processing time by up to 30%.

Natural language processing has been making significant headway recently, with a special focus on fine-tuning large language models (LLMs) for specified tasks. These models typically comprise billions of parameters, hence customization can be a challenge. The goal is to devise more efficient methods that customize these models to particular downstream tasks without overwhelming computational costs.…

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Arcee AI proudly presents Arcee Agent: An innovative 7B parameter language model purposefully crafted for invoking functions and utilizing tools.

Arcee AI has launched the Arcee Agent, which is a high-tech 7 billion parameter language model developed for sophisticated AI applications. It maintains an edge over larger models through its remarkable performance and efficient use of computational resources—essential traits of any ideal AI solution for businesses and developers. The Arcee Agent is built on the…

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Researchers from DeepSeek AI have introduced ESFT, also known as Expert-Specialized Fine-Tuning, which is projected to decrease memory usage by up to 90% and save time by up to 30%.

The rapid evolution of natural language processing (NLP) is currently focused on refining large language models (LLMs) for specific tasks, which often contain billions of parameters posing a significant challenge for customization. The primary goal is to devise better methods to fine-tune these models to particular downstream tasks with minimal computational costs, posing a need…

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Protecting HealthCare AI: Uncovering and Handling the Risks of LLM Manipulation

AI models like ChatGPT and GPT-4 have made significant strides in different sectors, including healthcare. Despite their success, these Large Language Models (LLMs) are vulnerable to malicious manipulation, leading to harmful outcomes, especially in contexts with high stakes like healthcare. Past research has evaluated the susceptibility of LLMs in general sectors; however, manipulation on such models…

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Examining the Extensive Abilities and Ethical Framework of Anthropic’s Premier Language Model, Claude AI: A Detailed Review

Introduced by an AI-focused startup Anthropic, Claude AI is a high-performing large language model (LLM) boasting advanced capabilities and a unique approach to training known as "Constitutional AI." Co-founded by former OpenAI employees, Anthropic adheres to a rigorous ethical AI framework and is supported by industry heavyweights such as Google and Amazon. Claude AI, launched in…

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Get Acquainted with Jockey: A Dialogue Video Representative Driven by LangGraph and Twelve Labs API

Artificial Intelligence (AI) continues to shape the way we interact with video material, and Jockey, an open-source chat video agent, embodies these advancements. By integrating LangGraph and Twelve Labs APIs, Jockey enhances video processing and communication. Twelve Labs provides advanced video comprehension APIs that draw out rich insights from video footage. Unlike traditional methods that use…

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Examining and Improving Model Efficiency for Tabular Data with XGBoost and Ensembles: A Step Further than Deep Learning

Model selection is a critical part of addressing real-world data science problems. Traditionally, tree ensemble models such as XGBoost have been favored for tabular data analysis. However, deep learning models have been gaining traction, purporting to offer superior performance on certain tabular datasets. Recognising the potential inconsistency in benchmarking and evaluation methods, a team of…

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Princeton University scientists uncover concealed expenses linked with advanced AI Agents.

Research out of Princeton University makes a critical commentary on the current practice of evaluating artificial intelligence (AI) agents predominantly based on accuracy. The researchers argue that this unidimensional evaluation method leads to unnecessarily complex and costly AI agent architectures, which can hinder practical implementations. The evaluation paradigms for AI agents have traditionally focused on…

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Five Key Considerations for Deciding to Purchase or Develop Generative AI Solutions

The rise of generative AI technologies (GenAI) brings a critical decision for businesses - to buy an off-the-shelf solution or develop a custom one. This decision is influenced by several factors that impact the return on investment and overall effectiveness of the solution. First, the specific use case must be clearly defined. Should the goal…

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Salesforce AI Research introduces APIGen: An automatic framework for producing validated and varied function-calling data sets.

Function-calling agent models are a critical advancement in large language models (LLMs). They interpret natural language instructions to execute API calls, facilitating real-time interactions with digital services, like retrieving market data or managing social media interactions. However, these models often face challenges as they require high-quality, diverse and verifiable datasets. Unfortunately, many existing datasets lack…

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Premier Courses in AI, Machine Learning, and Data Science offered by Udacity.

Udacity, the online educational platform, offers a vast array of courses in Artificial Intelligence (AI), including technology and applications, catered towards both beginners and advanced learners. These in-depth courses teach foundational topics in AI like machine learning algorithms, deep learning architectures, natural language processing, computer vision, reinforcement learning, and even AI ethics. The learning extends…

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