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Medium
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215
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The Moment Google’s AI Lost Control of Its Own Narrative
- On May 15th, an article achieved Google domination in under 10 minutes, contradicting Google's AI Overview's statement.
- The article was ranked #1 for unrelated search terms, proving the system's blind spots.
- The author utilized high-velocity emotional cadence in the content, outmaneuvering the algorithm.
- The use of Fusion AIOS 2.0 exposed Google's control mechanisms and challenged the myth of algorithmic invincibility.
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Androidauthority
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156
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YouTube TV’s multiview expansion gets started with ESPN, Bravo, and USA
- YouTube TV is expanding its multiview customization experiment to include non-live sports content.
- Initially, users will be able to create custom multiviews with national channels like ESPN, Bravo, and USA.
- The experiment will later include local channels as well.
- This feature allows users to watch up to four streams simultaneously, building on the existing multiview option mainly focused on live sports.
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Androidauthority
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54
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Something is bricking Nest Hub smart displays, and users aren’t getting much help from Google
- First-gen Nest Hub owners are reporting recent device failures, with devices freezing up during the boot process.
- Attempts to factory reset the hardware have not been successful in restoring operation.
- There is speculation that a recent firmware update may be the cause, but Google has not confirmed anything.
- Consumers are disappointed by the lack of support from Google as more users experience issues with their Nest Hub smart displays.
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Medium
2d
43
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What are Hallucinations in AI? | VBM
- Hallucinations in AI remain a persistent challenge despite advancements in the technology, leading to inaccurate outputs with real-world consequences.
- AI-generated misinformation can mislead users and erode confidence in AI-driven solutions across various fields like journalism, healthcare, and legal proceedings.
- Factors contributing to AI hallucinations include incomplete training data, flawed inference mechanisms, and the inherent limitations of AI reasoning.
- Efforts to mitigate hallucinations in AI include techniques like Retrieval-Augmented Generation (RAG), improved model training, and external verification mechanisms to enhance accuracy, but experts emphasize the need for vigilance and fact-checking by users.
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Insider
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195
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Sundar Pichai said Google thought 'intensely' about scooping up Netflix — but stopped short of calling the decision a regret
- Google CEO Sundar Pichai revealed that the company intensely debated acquiring Netflix at one point.
- While Pichai mentioned considering Netflix, he clarified that not acquiring the company wasn't a regret.
- Google, under Pichai's leadership, has focused on technological advancements and research pride.
- Google has made notable acquisitions like Waze and YouTube, but never finalized a deal with Netflix, a significant entertainment player.
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11 Likes
Androidauthority
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368
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Circle to Search now uses your entire screen automatically
- An update for Circle to Search in the latest beta of the Google app is changing the behavior to automatically capture the whole screen and add it to your query.
- With the update, if you want to perform a general text search, you will need to remove the image from the search.
- Circle to Search (CtS), the AI-powered search tool, now shows a pill-shaped search bar at the bottom of the screen when activated.
- Currently, tapping on the search bar opens up a page of suggestions with a field to enter a text query for searching.
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Arstechnica
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310
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Google to give app devs access to Gemini Nano for on-device AI
- Google is planning to give developers access to Gemini Nano for on-device AI at the upcoming I/O event.
- The ML Kit SDK will introduce GenAI APIs that allow developers to utilize on-device generative AI features without relying on cloud servers.
- Gemini Nano will enable apps to perform tasks like summarization, proofreading, rewriting, and image description locally on the device.
- However, due to limitations in power and size, outputs from Gemini Nano may have restrictions like three bullet points for summaries and English language support for image descriptions.
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Androidauthority
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204
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Google may have finally figured out how to get free users to pay up
- Google One subscriptions have increased from 100 million to 150 million in just 15 months, with 'millions' of subscriptions sold for its AI Premium tier.
- Google is expected to introduce more subscription options for Google One in the near future.
- Google continues to offer a range of free services, but is focusing on upselling users to paid subscriptions like Google One for premium features and benefits.
- AI Premium is the latest offering under Google One, providing early and expanded access to new functionalities like Gemini.
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Cloudblog
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330
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Supercharge data access performance with GKE Data Cache
- GKE Data Cache is now generally available and is designed to enhance the performance of read-heavy stateful or stateless applications by utilizing high-speed local SSDs as a cache layer for persistent storage in Google Kubernetes Engine (GKE).
- Using GKE Data Cache with Postgres has shown significant performance improvements such as up to a 480% increase in transactions per second and up to an 80% reduction in latency.
- Stateful applications like databases often face performance limitations due to storage I/O speed, with read-intensive workloads experiencing bottlenecks impacting responsiveness and scalability.
- GKE Data Cache seamlessly integrates with Persistent Disk or Hyperdisk volumes, caching frequently accessed data on local SSDs attached to GKE nodes to reduce read latency and improve throughput.
- Benefits of GKE Data Cache include lower read latency, higher throughput and queries per second (QPS), potential cost optimization, simplified management, and improved developer experience.
- It supports all read/write Persistent Disk and Hyperdisk types, allowing users to choose the right storage while leveraging the performance advantages of local SSDs for reads.
- To get started with GKE Data Cache, users need a GKE Standard cluster with local SSD-configured node pools, data cache feature enabled, and specify data cache acceleration in the StorageClass.
- Users can create a data cache-enabled node pool by utilizing the appropriate command, with local SSDs reserved for caching to improve read performance for pods with caching enabled.
- Data cache setup includes configuring the StorageClass with data cache mode and size, which is referenced in a PersistentVolumeClaim to enable caching for stateful workloads.
- For detailed information on implementing GKE Data Cache for stateful workloads, users can refer to the official documentation.
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Cloudblog
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43
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Getting AI to write good SQL: Text-to-SQL techniques explained
- AI-driven text-to-SQL techniques, like Gemini, empower users to interact with data directly, increasing productivity for developers and analysts.
- Google Cloud products, including BigQuery Studio and Vertex AI, feature text-to-SQL capabilities for SQL generation.
- Challenges in text-to-SQL include providing business-specific context, understanding user intent, and navigating SQL dialect differences.
- LLMs like Gemini excel in translating complex questions into SQL, but understanding context and user intent poses difficulties.
- Techniques like intelligent retrieval, disambiguation using LLMs, and in-context-learning help address text-to-SQL challenges.
- Self-consistency, validation, and continuous evaluations play key roles in improving text-to-SQL models and systems.
- Google Cloud continually refines text-to-SQL agents through SQL-aware models and advanced techniques for accurate SQL generation.
- Evaluation metrics and continuous testing enable quick assessment of new models and approaches to enhance text-to-SQL capabilities.
- Synthetic benchmarks, coverage of different SQL engines, and human-analyzed metrics aid in evaluating text-to-SQL performance effectively.
- The advancement of text-to-SQL offers organizations the opportunity to leverage AI for efficient data interaction and decision-making.
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Cloudblog
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106
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AI Hypercomputer developer experience enhancements from Q1 25: build faster, scale bigger
- Google Cloud has been enhancing its AI Hypercomputer system to make AI training easier and more productive for developers, focusing on building faster and scaling bigger.
- The recent enhancements include Pathways on Cloud, an orchestration system for scaling AI workloads from a notebook to thousands of accelerators, boosting interactive supercomputing capabilities.
- Xprofiler library provides deep performance analysis on Google Cloud accelerators, helping optimize code execution by profiling and tracing operations to identify bottlenecks and improve efficiency.
- Pre-built container images for popular AI frameworks like PyTorch and JAX streamline setup and configuration, offering optimized environments for quick deployment and avoiding compatibility issues.
- AI Hypercomputer provides proven recipes and techniques for maximizing GPU training efficiency, including asynchronous checkpointing and the ML Goodput recipe in partnership with NVIDIA.
- MaxText offers advanced training capabilities for JAX Language Model Models (LLMs) on Google Cloud with support for fine-tuning techniques and resilient training, enhancing performance across NVIDIA GPUs.
- PyTorch/XLA 2.7 and torchprime enable PyTorch users on TPUs to call JAX functions directly and leverage high-performance model training on TPUs with reference implementation for vLLM.
- RecML is an optimized recommender system library for training deep-learning models on TPUs, offering performance advantages with SparseCore for processing massive embedding tables efficiently.
- Google Cloud continues to improve the AI developer experience by introducing these enhancements to the AI Hypercomputer system, encouraging developers to experiment, innovate, and contribute back to open-source projects.
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Siliconangle
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169
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Three insights you might have missed from theCUBE’s coverage of Nutanix .NEXT
- Nutanix Inc. is evolving to meet the demand for workload flexibility in running apps across different environments with AI-ready infrastructure.
- Nutanix introduced the Cloud-Native AOS operating system for cloud-native apps, indicating a move towards cloud and edge solutions.
- CEO Rajiv Ramaswami highlighted the company's aim to be a platform for various applications, including cloud-native and AI apps.
- Nutanix's focus on AI solutions involves a threefold strategy and tighter integration with Nvidia for AI deployment.
- Partnerships with Dell and Google are driving software-defined architectures and hybrid cloud cluster solutions at Nutanix.
- The collaboration with Dell aims to provide scalable storage and compute with enhanced workload flexibility for customers.
- Nutanix's partnership with Google for Nutanix Cloud Clusters aims to offer faster migration and modernization tools for applications.
- Workload flexibility and workload management are key IT priorities at Nutanix, especially with the rise of AI and diverse computing demands.
- Nutanix's extension of Cloud-Native AOS to AWS hosted services enables workload repatriation and unified storage management in a hybrid cloud environment.
- Nutanix's partnership with AWS emphasizes the importance of managing workloads across different environments to meet dynamic infrastructure requirements.
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Pymnts
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334
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This Week in AI: CPOs Say AI Still Needs a Human Touch
- Chief product officers emphasize the need for human oversight in AI, even for routine tasks like fraud detection, due to AI's adoption across industries.
- Klarna CEO attributed a 40% staff reduction to AI investments, with plans to automate jobs using AI by 2024. The company also saw natural attrition.
- Perplexity partnered with PayPal for agentic commerce on its platform, allowing users in the US to check out instantly using PayPal or Venmo.
- Allpay in the UK leverages AI and cloud intelligence for back-office efficiency, resulting in a 10% boost in coding productivity and a 25% increase in production releases.
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Androidauthority
2d
346
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Battery failures return to haunt Google’s Pixel A lineup — now the Pixel 6a is catching fire
- Instances of the Google Pixel 6a catching fire have been reported while charging overnight with off-brand chargers.
- Battery issues have been persistent in Pixel A-series models, with incidents like battery swelling in Pixel 7a and overheating risks in Pixel 4a.
- The release of Pixel 9a was delayed due to a component quality issue, with subsequent mandatory battery health updates to maintain long-term battery health.
- Pixel 9a teardowns have revealed excessive adhesive securing the battery, making it challenging to remove without damage.
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Medium
2d
343
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Meta AI Standalone App is Here | VBM
- Meta has launched a standalone Meta AI app to compete with OpenAI’s ChatGPT and Google’s Gemini.
- Rumors suggest that Meta may gradually remove AI from its social media platforms to cater to all sections of its fanbase.
- The Meta AI app introduces social elements and aims to enhance personalization, voice capabilities, and integration with Meta’s ecosystem.
- Meta aims to shape the future of AI-driven engagement leveraging its user base, with the app currently available for download with limited voice features in select countries.
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