MarkTechPost » Artificial Intelligence
2,336 FOLLOWERS
MarkTechPost reports related subjects such as artificial intelligence, blockchain technology, and healthcare. Marktechpost is a California-based AI News Platform providing easy-to-consume, byte size updates in machine learning, deep learning, and data science research.
MarkTechPost » Artificial Intelligence
10h ago
Artificial intelligence (AI) has introduced a dynamic shift in various sectors, most notably by deploying autonomous agents capable of independent operation and decision-making. These agents, powered by large language models (LLMs), have significantly broadened the scope of tasks that can be automated, ranging from simple data processing to complex problem-solving scenarios. However, as the capabilities of these agents expand, so do the challenges associated with their deployment and integration.
Within this evolving landscape, a major hurdle has been the efficient management of LLM-based age ..read more
MarkTechPost » Artificial Intelligence
12h ago
With the recent advancements in the field of Machine Learning (ML), Reinforcement Learning (RL), which is one of its branches, has become significantly popular. In RL, an agent picks up skills to interact with its surroundings by acting in a way that maximizes the sum of its rewards.
The incorporation of world models into RL has emerged as a potent paradigm in recent years. Agents may observe, simulate, and plan within the learned dynamics with the help of the world models, which encapsulate the dynamics of the surrounding environment. Model-Based Reinforcement Learning (MBRL) has been ..read more
MarkTechPost » Artificial Intelligence
14h ago
Artificial Intelligence (AI) has been making significant strides over the past few years, with the emergence of Large Language Models (LLMs) marking a major milestone in its growth. With such widespread adoption, feeling left out of this revolution is not uncommon. One way an individual can stay updated with the latest trends is by reading books on various facets of AI. Following are the top AI books one should read in 2024.
Deep Learning (Adaptive Computation and Machine Learning series)
This book covers a wide range of deep learning topics along with their mathematical and conceptual backgr ..read more
MarkTechPost » Artificial Intelligence
14h ago
LLMs have shown remarkable capabilities but are often too large for consumer devices. Smaller models are trained alongside larger ones, or compression techniques are applied to make them more efficient. While compressing models can significantly speed up inference without sacrificing much performance, the effectiveness of smaller models varies across different trust dimensions. Some studies suggest benefits like reduced biases and privacy risks, while others highlight vulnerabilities like attack susceptibility. Assessing compressed models’ trustworthiness is crucial, as current evaluations of ..read more
MarkTechPost » Artificial Intelligence
16h ago
In machine learning, one method that has consistently demonstrated its worth across various applications is the Support Vector Machine (SVM). Known for its adeptness at parsing through high-dimensional spaces, SVM is designed to draw an optimal dividing line, or hyperplane, between data points belonging to different classes. This hyperplane is critical as it allows predictions about new, unseen data, emphasizing SVM’s strength in creating models that generalize well beyond the training data.
A persistent challenge within SVM approaches concerns how to handle samples that are either misc ..read more
MarkTechPost » Artificial Intelligence
19h ago
Symmetry is a fundamental characteristic where an object remains unchanged under certain transformations and is a key inductive bias that enhances model performance and efficiency. Therefore, understanding and leveraging the concept of symmetry has emerged as a cornerstone for designing more efficient and effective neural network models. Researchers have consistently sought ways to exploit this property, leading to significant breakthroughs that span various machine-learning applications.
One of the main challenges identified in this domain is the limitation of equivariant functions in neural ..read more
MarkTechPost » Artificial Intelligence
20h ago
Language models’ evolution is shifting from Large Language Models (LLMs) to the era of Small Language Models (SLMs). At the core of both LLMs and SLMs lies the power of transformers, which are the building blocks of LLMs and SLMs. While transformers have proven their outstanding performance across domains through their attention networks, multiple issues exist in attention networks, including low inductive bias and quadratic complexity concerning input sequence length.
State Space Models (SSMs) like S4 and others have emerged to address the above issues and help handle longer sequence l ..read more
MarkTechPost » Artificial Intelligence
22h ago
In a new AI research paper, a team of researchers from Stanford Law School has investigated biases present in state-of-the-art large language models (LLMs), including GPT-4, focusing particularly on disparities related to race and gender. It highlights the potential harm caused by biases encoded in these models, especially when providing advice across various scenarios, such as car purchase negotiations or election outcome predictions. The paper aims to shed light on the systemic nature of biases in LLMs and propose methods to mitigate their harmful effects on marginalized communities.
Curren ..read more
MarkTechPost » Artificial Intelligence
22h ago
On social media, toxic speech can spread like wildfire, targeting individuals and marginalized groups. While explicit hate is relatively easy to flag, implicit toxicity – which relies on stereotypes and coded language rather than overt slurs – poses a trickier challenge. How do we train AI systems to not only detect this veiled toxicity but also explain why it’s harmful?
Researchers at Nanyang Technological University, Singapore, National University of Singapore, and Institute for Infocomm Research have tackled this head-on with a novel framework called ToXCL, an overview of which is shown in ..read more
MarkTechPost » Artificial Intelligence
1d ago
In today’s digital age, software developers and product teams are inundated with user feedback from various channels – app reviews, forum posts, social media comments, and more. This wealth of verbatim feedback holds the key to understanding user experiences, identifying pain points, and uncovering opportunities for improvement. However, sifting through thousands of text-based reviews across multiple platforms and languages can be overwhelming and time-consuming, often leaving valuable insights buried beneath the sheer volume of data. Traditional methods for feedback analysis have relied heav ..read more