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…
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…
Language modeling in the area of artificial intelligence is geared towards creating systems capable of understanding, interpreting, and generating human language. With its myriad applications, including machine translation, text summarization, and creation of conversational agents, the goal is to develop models that mimic human language abilities, thereby fostering seamless interaction between humans and machines. This…
ChatGPT and similar AI-powered tools are now vital in the modern business environment. They offer a multitude of benefits, allowing businesses to gain a competitive edge, boost productivity, and enhance their profit margins. In this article, 10 key use cases for ChatGPT that professionals, CxOs, and business owners can adopt extensively have been identified.
ChatGPT's application…
Large language models (LLMs) are becoming progressively more powerful, with recent models exhibiting GPT-4 level performance. Nevertheless, using these models for applications requiring extensive context, such as understanding long-duration videos or coding at repository-scale, presents significant hurdles. Typically, these tasks require input contexts ranging from 100K to 10M tokens — a great leap from the…
Qdrant, a pioneer in vector search technology, has unveiled BM42, a powerful new algorithm, aimed at transforming hybrid search. BM25, the algorithm relied upon by search engines like Google and Yahoo, has dominated for over 40 years. Yet, the rise of vector search and the launch of Retrieval-Augmented Generation (RAG) technologies have revealed the need…
Researchers from Stanford University have developed a new model to investigate the contributions of individual data points to machine learning processes. This allows an understanding of how the value of each data point changes as the scale of the dataset grows, illustrating that some points are more useful in smaller datasets, while others become more…
Polkadot, a blockchain platform with a market cap of $8 billion, released its H1 2024 Treasury report revealing massive spending in marketing and promotional activities. The details expose the company's high expenses, with the Treasury spending $87 million in the first half of 2024 alone. Most notable was the allocation of $37 million in "Outreach",…
Overfitting is a prevalent problem when training large neural networks on limited data. It indicates a model's strong performance on the training data but its failure to perform comparably on unseen test data. This issue arises when the network’s feature detectors become overly specialized to the training data, building complex dependencies that do not apply…
The computer vision sector is currently dominated by large-scale models that offer remarkable performance but demand high computational resources, making them impractical for real-world applications. To address this, the Google Research Team has opted to reduce these models into smaller, more efficient architectures via model pruning and knowledge distillation. The team's focus is on knowledge…
The evolution of Large Language Models (LLMs) in artificial intelligence has spawned several sub-groups, including Multi-Modal LLMs, Open-Source LLMs, Domain-specific LLMs, LLM Agents, Smaller LLMs, and Non-Transformer LLMs.
Multi-Modal LLMs, such as OpenAI's Sora, Google's Gemini, and LLaVA, consolidate various types of input like images, videos, and text to perform more sophisticated tasks. OpenAI's Sora…
The creation and implementation of effective AI agents have become a vital point of interest in the Language Learning Model (LLM) field. AI company, Anthropic, recently spotlighted several successful design patterns being employed in practical applications. Discussed in relation to Claude's models, these patterns offer transferable insights for other LLMs. Five key design patterns examined…