Long-Context Question Answering (LCQA), a challenging task, aims to reason over long-context documents to yield accurate answers to questions. Existing long-context Large Language Models (LLMs) for LCQA often struggle with the "lost in the middle" issue. Retrieval-Augmented Generation (RAG) mitigates this issue by providing external factual evidence. However, its chunking strategy disrupts the global long-context information, and its low-quality retrieval in long contexts hinders LLMs from identifying effective factual details due to substantial noise. To this end, we propose LongRAG, a general, dual-perspective, and robust LLM-based RAG system paradigm for LCQA to enhance RAG's understanding of complex long-context knowledge (i.e., global information and factual details). We design LongRAG as a plug-and-play paradigm, facilitating adaptation to various domains and LLMs. Extensive experiments on three multi-hop datasets demonstrate that LongRAG significantly outperforms long-context LLMs (up by 6.94%), advanced RAG (up by 6.16%), and Vanilla RAG (up by 17.25%). Furthermore, we conduct quantitative ablation studies and multi-dimensional analyses, highlighting the effectiveness of the system's components and fine-tuning strategies. Data and code are available at https://github.com/QingFei1/LongRAG.

The application of Artificial Intelligence in the medical market brings up increasing concerns but aids in more timely diagnosis of silent progressing diseases like Diabetic Retinopathy. In order to diagnose Diabetic Retinopathy (DR), ophthalmologists use color fundus images, or pictures of the back of the retina, to identify small distinct features through a difficult and time-consuming process. Our work creates a novel CNN model and identifies the severity of DR through fundus image input. We classified 4 known DR features, including micro-aneurysms, cotton wools, exudates, and hemorrhages, through convolutional layers and were able to provide an accurate diagnostic without additional user input. The proposed model is more interpretable and robust to overfitting. We present initial results with a sensitivity of 97% and an accuracy of 71%. Our contribution is an interpretable model with similar accuracy to more complex models. With that, our model advances the field of DR detection and proves to be a key step towards AI-focused medical diagnosis.

For the last decade, Amazon has been building an army of robot employees to sort packages and move products safely around its warehouses. Now the company has unveiled its latest robot called Proteus, which it describes as its'first fully autonomous mobile robot'. Proteus is designed to work alongside humans, moving large trolleys full of packages around the warehouse floor. The robot uses Amazon's own safety, perception, and navigation technology to move around autonomously and avoid bumping into human workers. 'Historically, it's been difficult to safely incorporate robotics in the same physical space as people,' the company said in a blog post.

A new report reveals that robots working in Amazon fulfillment centers are leading to more injuries among human employees - although the e-commerce giant claims the technology reduces incidents. Based on internal records from 150 warehouses, serious injuries were 50 percent higher at facilities with robots than those without, according to the Center for Investigative Reporting's news site, Reveal. There were 14,000 serious injuries in 2019 - a spike of nearly 33 percent from 2015, and nearly double the industry average. The overall injury rate for the 150 facilities was also almost double the industry standard, according to Reveal. Amazon insisted its numbers are inflated because it encourages workers to report even minor incidents.

Guess who's getting used to working with robots in their everyday lives? The very same warehouse workers once predicted to be losing their jobs to mechanical replacements. According to their makers, the machines should take on the most mundane and physically strenuous tasks. "They weigh a lot," Amazon worker Amanda Taillon said during the pre-Christmas rush at a company warehouse in Connecticut. Taillon's job is to enter a cage and tame Amazon's wheeled warehouse robots for long enough to pick up a fallen toy or relieve a traffic jam. She straps on a light-up utility belt that works like a superhero's force field, commanding the nearest robots to abruptly halt and the others to slow down or adjust their routes.

Guess who's getting used to working with robots in their everyday lives? The very same warehouse workers once predicted to be losing their jobs to mechanical replacements. According to their makers, the machines should take on the most mundane and physically strenuous tasks. "They weigh a lot," Amazon worker Amanda Taillon said during the pre-Christmas rush at a company warehouse in Connecticut. Taillon's job is to enter a cage and tame Amazon's wheeled warehouse robots for long enough to pick up a fallen toy or relieve a traffic jam. She straps on a light-up utility belt that works like a superhero's force field, commanding the nearest robots to abruptly halt and the others to slow down or adjust their routes.

Amazon has admitted that employees listen to customer voice recordings from Echo and other Alexa-enabled smart speakers. The online retail giant said its staff "reviewed" a sample of Alexa voice assistant conversations in order to improve speech recognition. "This information helps us train our speech recognition and natural language understanding systems, so Alexa can better understand your requests, and ensure the service works well for everyone," Amazon said in a statement. We'll tell you what's true. You can form your own view.

Amazon has launched a new robot delivery service in the US using a six wheeled machine that is "the size of a small cooler". The Amazon Scout uses self-driving technology to navigate through neighbourhoods to deliver packages to Amazon Prime customers, though its initial roll out is limited. The first deliveries are taking place in Snohomish County, just to the north of Amazon's headquarters in Seattle, Washington. Deliveries will be limited to daylight hours between Monday and Friday amd only six of the Scout delivery robots will be deployed at first. Each will also be accompanied by an Amazon employee to ensure they can safely navigate around any pedestrians or pets it might come across.

Amazon has developed a piece of wearable technology for its workers that will protect them from robot-related accidents. The Robotic Tech Vest is designed for Amazon employees working in warehouse fulfilment centres alongside autonomous robots. Featuring built-in sensors, the electronic belt provides warning alerts to nearby robots to inform them of a worker's presence. Its deployment across more than 25 Amazon sites follows incidents in which workers were injured as a result of a robot's actions. In December, 24 Amazon workers at a warehouse in New Jersey were hospitalised after a robot reportedly punctured a can of bear repellent.

Amazon Echo devices were hit by a major outage on Christmas Day after new owners reported issues with the smart home speaker. Users in the UK and across Europe took to social media to complain of difficulties in setting up the Alexa voice assistant, with some suggesting that the large number of new owners attempting to connect. "Good luck to everyone who was delighted to receive their Amazon Echo this morning," one person wrote on Twitter. "Amazon has been a victim of its own success. Imagine the fun that new owners have been experiencing this morning, unsure as to why their new gadget isn't working."