This holiday season, more shoppers are expected to use chatbots to figure out what to buy. This holiday season, rather than searching on Google, more Americans will likely be turning to large language models to find gifts, deals, and sales. Retailers could see up to a 520 percent increase in traffic from chatbots and AI search engines this year compared to 2024, according to a recent shopping report from Adobe . OpenAI is already moving to capitalize on the trend: Last week, the ChatGPT maker announced a major partnership with Walmart that will allow users to buy goods directly within the chat window. As people start relying on chatbots to discover new products, retailers are having to rethink their approach to online marketing.

The rapid adoption of generative AI-powered search engines like ChatGPT, Perplexity, and Gemini is fundamentally reshaping information retrieval, moving from traditional ranked lists to synthesized, citation-backed answers. This shift challenges established Search Engine Optimization (SEO) practices and necessitates a new paradigm, which we term Generative Engine Optimization (GEO). This paper presents a comprehensive comparative analysis of AI Search and traditional web search (Google). Through a series of large-scale, controlled experiments across multiple verticals, languages, and query paraphrases, we quantify critical differences in how these systems source information. Our key findings reveal that AI Search exhibit a systematic and overwhelming bias towards Earned media (third-party, authoritative sources) over Brand-owned and Social content, a stark contrast to Google's more balanced mix. We further demonstrate that AI Search services differ significantly from each other in their domain diversity, freshness, cross-language stability, and sensitivity to phrasing. Based on these empirical results, we formulate a strategic GEO agenda. We provide actionable guidance for practitioners, emphasizing the critical need to: (1) engineer content for machine scannability and justification, (2) dominate earned media to build AI-perceived authority, (3) adopt engine-specific and language-aware strategies, and (4) overcome the inherent "big brand bias" for niche players. Our work provides the foundational empirical analysis and a strategic framework for achieving visibility in the new generative search landscape.

With the advent of 5G networks and technologies, ensuring the integrity and performance of packet core traffic is paramount. During network analysis, test files such as Packet Capture (PCAP) files and log files will contain errors if present in the system that must be resolved for better overall network performance, such as connectivity strength and handover quality. Current methods require numerous person-hours to sort out testing results and find the faults. This paper presents a novel AI/ML-driven Fault Analysis (FA) Engine designed to classify successful and faulty frames in PCAP files, specifically within the 5G packet core. The FA engine analyses network traffic using natural language processing techniques to identify anomalies and inefficiencies, significantly reducing the effort time required and increasing efficiency. The FA Engine also suggests steps to fix the issue using Generative AI via a Large Language Model (LLM) trained on several 5G packet core documents. The engine explains the details of the error from the domain perspective using documents such as the 3GPP standards and user documents regarding the internal conditions of the tests. Test results on the ML models show high classification accuracy on the test dataset when trained with 80-20 splits for the successful and failed PCAP files. Future scopes include extending the AI engine to incorporate 4G network traffic and other forms of network data, such as log text files and multimodal systems.

On Wednesday, Perplexity.ai debuted Comet, its first entry into the browser market that does away with Google and Microsoft's Bing in favor of its own search engine. Comet will be available for both Windows and macOS platforms, the company said. Perplexity has locked Comet behind a, um, perplexing pricing model. Although Comet is technically free, Perplexity has made it accessible for now via a waitlist. If you'd like to download it, you can wait for your turn to arrive or subscribe to Perplexity Max, the company's 200/mo plan that includes access to its latest AI models.

--Convolutional Neural Networks (CNNs) remain prevalent in computer vision applications, and FPGAs, known for their flexibility and energy efficiency, have become essential components in heterogeneous acceleration systems. AMD's V ersal ACAP architecture, tailored for AI applications, incorporates AI Engines (AIEs) to deliver high computational power . Nevertheless, the platform suffers from insufficient memory bandwidth, hindering the full utilization of the AIEs' theoretical performance. We design two computation units, Conv PE and DWC PE, to support different computational patterns. Each computation unit's data flow efficiently utilizes the data reuse opportunities to mitigate bandwidth bottlenecks. Additionally, we extend the functionality of each PE to utilize AIEs for non-convolutional operations, reducing resource overhead. Experiments on over 50 models show that compared to previous designs, our design provides 8 . At present, deep learning (DL) has profoundly integrated into our daily lives. Despite the emergence of new transformer-based neural networks, Convolutional Neural Networks (CNN) remain extensively employed owing to their proficiency in extracting local information from images in relatively smaller datasets. GPUs' efficient parallel processing is used to improve CNN inference, but their general-purpose design reduces energy efficiency. To improve accelerators' energy efficiency and throughput, custom CNN architectures have been proposed.

Believe it or not, AI is already subtly reshaping the PC. No, we're not talking about the microprocessor or integrated NPUs. There, progress has been slow and stuttering, as chip vendors and Microsoft work toward establishing an ecosystem of Copilot PCs. Instead, PC vendors are looking for ways to reinvent the familiar with AI capabilities. But we wanted to know what PC vendors thought about the future of the AI PCs they're building.

Believe it or not, AI is already subtly reshaping the PC. No, we're not talking about the microprocessor or integrated NPUs. There, progress has been slow and stuttering, as chip vendors and Microsoft work toward establishing an ecosystem of Copilot PCs. Instead, PC vendors are looking for ways to reinvent the familiar with AI capabilities. But we wanted to know what PC vendors thought about the future of the AI PCs they're building.

Databases are increasingly embracing AI to provide autonomous system optimization and intelligent in-database analytics, aiming to relieve end-user burdens across various industry sectors. Nonetheless, most existing approaches fail to account for the dynamic nature of databases, which renders them ineffective for real-world applications characterized by evolving data and workloads. This paper introduces NeurDB, an AI-powered autonomous database that deepens the fusion of AI and databases with adaptability to data and workload drift. NeurDB establishes a new in-database AI ecosystem that seamlessly integrates AI workflows within the database. This integration enables efficient and effective in-database AI analytics and fast-adaptive learned system components. Empirical evaluations demonstrate that NeurDB substantially outperforms existing solutions in managing AI analytics tasks, with the proposed learned components more effectively handling environmental dynamism than state-of-the-art approaches.

The AI PC, propelled by Intel's Meteor Lake, is almost here. So why should you care? Intel is building NPU AI inferencing engines into its processors beginning with its 14th-gen Core chip, Meteor Lake, also known as the Core Ultra. Robert Hallock, an AMD veteran now overseeing technical CPU marketing for Intel's microprocessors, said Tuesday that Intel's goal by 2025 is to ship 100 million "AI PCs," a term Intel CEO Pat Gelsinger began using in July. Intel announced the architecture behind the 14th-gen Core Ultra chip on Tuesday, the same day as Intel's Innovation conference began in San Jose.

New York attorney and writer Alexander Zubatov weighs in on how A.I. is rapidly changing society and says he's concerned about A.I. being used as a weapon against descent on'The Ingraham Angle.' News Corp CEO Robert Thomson blasted the left-wing bias and inaccuracies spewed out by AI generated content -- calling it "rubbish in, rubbish out" -- even as he warned the technology threatens to kill thousands more jobs across the news industry. Left-leaning media giants that dominate the news business have churned out stories for years that are not only riddled with errors, but also written with a left-wing slant. "People have to understand that AI is essentially retrospective," the media executive said during an appearance at the Goldman Sachs Communacopia and Technology Conference in San Francisco on Thursday. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? AI (Artificial Intelligence) letters and robot hand are placed on computer motherboard in this illustration taken on June 23, 2023.