Artificial Intelligence
OpenAI is planning to reduce costs for developers and enterprise users. The company is expected to introduce changes next month that will streamline software development and decrease costs. One notable upgrade is the integration of memory storage in OpenAI’s developer tools, which has the potential to reduce application development costs by up to 20 times.…
Bank of England representatives have expressed concerns about the potential threats that biased AI decision-making poses to the financial system. They have highlighted that algorithms can perpetuate biases found in datasets, leading to unfair treatment of consumers and professionals. The use of “biased or unfair AI” could expose companies to legal and reputational risks. Instances…
IBM has launched Threat Detection and Response Services, a solution to address the overwhelming volume of security alerts faced by organizations. Leveraging AI, the system can automatically escalate or close 85% of alerts, allowing security teams to focus on critical threats. It also offers an MITRE ATT&CK assessment for security posture comparison and seamless integration…
Neural networks use non-linear activation functions to enable them to model and fit complex functions. The most common activation function is the rectified linear unit (ReLU), but there are others such as sigmoid, tanh, and leaky ReLU. The choice of activation function depends on the specific problem and should be experimented with to find the…
Researchers have developed an algorithm that can rapidly halt a man-in-the-middle cyberattack on an unmanned military robot, with a 99% success rate, when tested in real-time.
Infatica is a notable player in the proxy industry, providing different types of proxy servers for businesses and individuals. This post discusses the top 5 alternatives and competitors to Infatica in 2023.
The rise of LLMs has made the Retrieval Augmented Generation (RAG) framework popular for building question-answering systems. However, without proper tuning and experimentation, these systems may not be reliable in production. This article explores the problems with the RAG framework and provides tips for improving its performance, including leveraging document metadata and fine-tuning hyperparameters.
The text discusses the feasibility of building a local chatbot using Llama2, LangChain, and Streamlit on a CPU. The author carries out a case study to test the performance of the chatbot and evaluates its limitations. The conclusion is that while it is possible to build a chatbot on a CPU, the limited tokens, long…
Researchers have proposed SMPLer-X, a generalist foundation model for 3D/4D human motion capture from monocular inputs. The model shows impressive generalization capabilities and outperforms previous benchmark results. The research highlights the need for more diverse and extensive datasets for accurate human pose and shape estimation. The researchers also emphasize the value of utilizing multiple datasets…
This article introduces the Builder design pattern in Python and explains its importance in writing clean and reusable code. The Builder pattern is part of the creational design pattern class and simplifies the creation of objects by breaking it down into individual steps. The article provides a code example demonstrating how to implement the Builder…
The text discusses the challenges faced by the computer vision community and highlights the development of multimodal foundation models with vision and vision-language capabilities. It explores various instructional strategies and introduces important multimodal conceptual frameworks and models such as CLIP, BEiT, CoCa, UniCL, MVP, and BEiTv2. The text also discusses T2I production, spatial controllability in…
The author discusses using a Bayesian framework to choose between two restaurants based on reviews. Initially, with no reviews, all ratings are equally likely. The author then updates these beliefs based on observed data, using the Dirichlet distribution. The posterior ratings of the two restaurants are calculated, and the probability that restaurant A is better…
Fine-tuning commercial language models (LLMs) can bypass safety measures and lead to dangerous responses. Researchers found that fine-tuning GPT-3.5 with malicious examples deactivated its safety switch. This raises concerns about the safety and liability of fine-tuned models. Even proprietary models like GPT-3.5 can be compromised through fine-tuning, highlighting the need for robust safety mechanisms. Achieving…
Researchers from SLAC National Accelerator Laboratory, Stanford University, MIT, and Toyota Research Institute have developed a new approach using computer vision to analyze X-ray movies of lithium-ion batteries. By analyzing every pixel, they were able to uncover new physical and chemical details of battery cycling, including the impact of carbon coating thickness on lithium-ion flow.…
Large language models like ChatGPT have the potential to transform various fields but integrating them into real-world products poses challenges. A powerful strategy called retrieval-augmented generation (RAG) has emerged, allowing connection to external information sources for more accurate outputs. Several articles explore the intricacies and practical considerations of working with RAG, helpful for those in…
AI-driven apps are becoming popular for enhancing professional online images. Apps like Remini, Try It On AI, and AI Suit Up use artificial intelligence to create polished profile photos. While some users find these images to be genuine and professional, others believe they appear noticeably artificial. Cost is a driving factor, as professional photo sessions…
Researchers from Microsoft and ETH Zurich have released a dataset called “HoloAssist” to address the challenges of developing AI assistants for real-world tasks. The dataset contains extensive recordings of participants collaborating on physical manipulation tasks, capturing various sensor modalities and annotations. The dataset enables the development of anticipatory and proactive AI assistants for real-world scenarios,…
Predictive policing uses advanced analytics and machine learning to anticipate crimes before they happen. By analyzing historical crime data and other relevant information, algorithms can identify patterns and hotspots of criminal activity. However, recent investigations have revealed failures and ethical concerns, highlighting biases and the potential for inaccurate predictions. The efficacy of predictive policing software,…
MedARC has developed MindEye, an AI model that can analyze fMRI scans and retrieve the exact original image the person was looking at, even if the images are similar. The model can also identify similar images from a large image database. While impressive, the fMRI data collection process and limited training data are challenges. Nevertheless,…
Text-to-image diffusion models have dominated generative tasks by producing high-quality outcomes. Recently, image-to-image transformation tasks have been guided by diffusion models with external image conditions. However, the iterative and time-consuming nature of diffusion models limits their practical use. Recent research proposes distillation techniques to speed up sampling and condense the models. A single-stage distillation method…