Unite.AI
MARCH 24, 2024
In a significant leap forward for artificial intelligence (AI), a team from the University of Geneva (UNIGE) has successfully developed a model that emulates a uniquely human trait: performing tasks based on verbal or written instructions and subsequently communicating them to others. This accomplishment addresses a long-standing challenge in AI, marking a milestone in the field’s evolution.
Analytics Vidhya
MARCH 24, 2024
Introduction The Artificial intelligence world is moving very fast, and AI engineers are at the forefront of this revolution. Companies of all stripes are embracing AI to gain a strategic advantage, creating a surge in demand for these skilled professionals. However, becoming an AI engineer isn’t just about having a technical mind; it requires a […] The post 8 Must Have Skills to Become an AI Engineer in 2024 appeared first on Analytics Vidhya.
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Marktechpost
MARCH 24, 2024
Large language models have revolutionized natural language processing, providing machines with human-like language abilities. However, despite their prowess, these models grapple with a crucial issue- the Reversal Curse. This term encapsulates their struggle to comprehend logical reversibility, where they often need to deduce that if ‘A has a feature B,’ it logically implies ‘B is a feature of A.’ This limitation poses a significant challenge in the pursuit of truly intel
Analytics Vidhya
MARCH 24, 2024
Introduction Floods disproportionately impact developing countries with sparse streamflow gauge networks, highlighting the need for accurate early warnings. The acceleration of flood-related disasters due to climate change underscores the urgency for effective early warning systems, especially in low- and middle-income countries where 90% of vulnerable populations reside.
Speaker: Scott Sehlhorst
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
Marktechpost
MARCH 24, 2024
Researchers are considering the fusion of large language models (LLMs) with AI agents as a significant leap forward in AI. These enhanced agents can now process information, interact with their environment, and execute multi-step actions, heralding a new era of task-solving capabilities. However, complexities are involved in developing and evaluating new reasoning strategies and agent architectures for LLM agents due to the intricacy of existing frameworks.
Artificial Intelligence Zone brings together the best content for AI and ML professionals from the widest variety of thought leaders.
Marktechpost
MARCH 24, 2024
Virtual assistant technology aims to create seamless and intuitive human-device interactions. However, the need for a specific trigger phrase or button press to initiate a command interrupts the fluidity of natural dialogue. Recognizing this challenge, Apple researchers have embarked on a groundbreaking study to enhance the intuitiveness of these interactions.
Towards AI
MARCH 24, 2024
Last Updated on March 25, 2024 by Editorial Team Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Large Language Models Research Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. This article summarizes some of the most important LLM papers published during the Third Week of March 2024.
Marktechpost
MARCH 24, 2024
Recent advancements in multimodal large language models (MLLM) have revolutionized various fields, leveraging the transformative capabilities of large-scale language models like ChatGPT. However, these models, primarily built on Transformer networks, suffer from quadratic computation complexity, hindering efficiency. Contrastingly, Language-Only Models (LLMs) are limited in adaptability due to their sole reliance on language interactions.
TheSequence
MARCH 24, 2024
Created Using DALL-E Next Week in The Sequence: Edge 381: We start a new series about autonomous agents! We introdice the main concepts in agents and review the AGENTS framework from ETH Zurich. Additionally, we provide an overview of BabyAGI. Edge 382: We review PromptBreeder, Google Deemind’s self-improving prompt technique. You can subscribe below: heSequence is a reader-supported publication.
Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage
Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.
Marktechpost
MARCH 24, 2024
In the evolving landscape of computational models for visual data processing, searching for models that balance efficiency with the ability to handle large-scale, high-resolution datasets is relentless. Though capable of generating impressive visual content, the conventional models grapple with scalability and computational efficiency, especially when deployed for high-resolution image and video generation.
Analytics Vidhya
MARCH 24, 2024
Introduction The ability to transform a single image into a detailed 3D model has long been a pursuit in the field of computer vision and generative AI. Stability AI’s TripoSR marks a significant leap forward in this quest, offering a revolutionary approach to 3D reconstruction from images. It empowers researchers, developers, and creatives with unparalleled […] The post Stability AI’s TripoSR: From Image to 3D Model in Seconds appeared first on Analytics Vidhya.
Marktechpost
MARCH 24, 2024
The artificial intelligence sector is seeing a surge in new entrants. Artificial intelligence’s application is revolutionizing technology in fields like NLP (Natural Language Processing) and ML (Machine Learning). The learning curve for artificial intelligence is steep, too, for those who aren’t enthusiastic about diving in. Traditional tools, like Jupyter Notebooks, can be difficult and intimidating to people new to data research.
Bugra Akyildiz
MARCH 24, 2024
Articles X.ai released the Grok’s first model and its weights in a very short blog post. Model is Jax based and it is available in GitHub , it uses mixture of experts model and it has a Transformer based architecture. Eagle 7B model is available as open source and this is an excellent and very efficient model that builds on top of RWKV, but what is RWKV?
Speaker: Anne Steiner and David Laribee
As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.
Marktechpost
MARCH 24, 2024
AI constantly evolves and needs efficient methods to integrate new knowledge into existing models. Rapid information generation means models can quickly become outdated, which has given birth to model editing. In this complex arena, the goal is to imbue AI models with the latest information without undermining their foundational structure or overall performance.
Robot Writers AI
MARCH 24, 2024
Expert users of multiple AI auto-writers, imagers and video-makers may want to check-out a new service that offers access to all those tools from a single, centralized dashboard. Dubbed BlendAI, the new platform — which offers one-stop access to popular AI tools like ChatGPT, Mistral and Stable Diffusion — also enables you to do side-by-side comparisons and ‘shoot-outs’ of those tools.
Marktechpost
MARCH 24, 2024
Large Language Models (LLMs) have been at the forefront of advancements in natural language processing, demonstrating remarkable abilities in understanding and generating human language. Despite these achievements, their capacity for complex reasoning, a critical aspect of various applications, remains a notable challenge. The research community, particularly a team from Renmin University of China and Université de Montréal, has sought to enhance this aspect, with Chain-of-Thought (CoT) promptin
Marktechpost
MARCH 24, 2024
Generating realistic human facial images has long challenged computer vision and machine learning researchers. Early techniques like Eigenfaces used Principal Component Analysis (PCA) to learn statistical priors from data but severely lacked the ability to capture the real-world complexities of lighting, expressions, and viewpoints beyond frontal poses.
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Marktechpost
MARCH 24, 2024
Researchers address the challenge of integrating machine learning frameworks with diverse hardware architectures efficiently. The existing integration process has been complex and time-consuming, and there is often a lack of standardized interfaces that leads to compatibility issues and hinders the adoption of new hardware technologies. Developers were required to write specific code for each hardware device.
Marktechpost
MARCH 24, 2024
A recent development of a model merging into the community of large language models (LLMs) presents a paradigm shift. Strategically combining multiple LLMs into a single architecture, this development approach has captivated the attention of researchers mainly due to the advantage that it requires no additional training, which cuts the cost of building new models significantly.
Marktechpost
MARCH 24, 2024
In machine learning and artificial intelligence, training large language models (LLMs) like those used for understanding and generating human-like text is time-consuming and resource-intensive. The speed at which these models learn from data and improve their abilities directly impacts how quickly new and more advanced AI applications can be developed and deployed.
Marktechpost
MARCH 24, 2024
In recent research, a team of researchers has introduced Jan , an open-source ChatGPT alternative that runs locally on the computer. The introduction of Jan is a major advancement in the field of Artificial Intelligence (AI) that is geared towards democratizing access to AI technologies. Jan enables having the power of ChatGPT locally on the desktop, with all preferred models, configurations, and functionalities.
Speaker: David Bard, Principal at VP Product Coaching
In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.
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