Latest news with #AdamSelipsky
Forbes
02-05-2025
- Business
- Forbes
Top 5 Decentralized Data Collection Providers In 2025 For AI Business
Adam Selipsky CEO of Amazon Web Service (AWS), speaking at the Keynote: Delivering a new World, ... More Barcelona, Spain, on March 01 2022. (Photo by Joan Cros/NurPhoto via Getty Images) The world runs on data, and businesses increasingly rely on it. However, traditional data sourcing methods often present challenges related to diversity, transparency, privacy, and cost. This article reviews the current state of decentralized data collection and outlines key steps for wisely selecting a decentralized data provider—along with a shortlist of top options to consider. Traditionally, centralized data collection involves gathering data from various sources—such as apps, devices, or websites—and sending it to a single central server or database controlled by one organization. This data is collected via APIs, sensors, tracking tools, or manual input. The biggest bottleneck of this model for AI's future and for businesses is the inability to collect truly 'global' and 'diverse' data from different regions and cultures. Decentralized data collection addresses this by leveraging blockchain technology. It enables small-scale cross-border payments which encourages global users to contribute data voluntarily in exchange for incentives—something that centralized or Web2 platforms cannot achieve. Another key aspect is transparency. Centralized AI and data collection are often criticized for operating as " black boxes," lacking transparency and accountability. People have no idea how and where they collect these data for their business. Furthermore, it's difficult to verify whether data is collected lawfully and ethically. In contrast, decentralized data collection enhances transparency by recording the data collection process on blockchain and storing data across multiple independent nodes rather than under a single authority. This blockchain-powered structure allows users to trace how and where their data is used efficiently, reduces the risk of hidden manipulation, and ensures that no single party can alter or monopolize the data without broad consensus. As a result, decentralized solutions are emerging as a strong alternative for businesses seeking more robust data strategies. By leveraging blockchain technology, decentralized data collection enhances both data diversity and verifiability, opening access to new, previously untapped data sources. Businesses interested in exploring decentralized data collection should: Below are five noteworthy platforms operating in the decentralized data collection space, outlining their core functionalities and potential business applications. Core offering: Decentralized data marketplace for AI and ML datasets. Strengths: Best for: Anyone looking to buy/sell datasets or run compute-to-data workloads. Example: access a specific medical imaging dataset to train a diagnostic AI, with the data provider maintaining control over the data itself. Website: Core offering: Decentralized knowledge agent platform and AI data marketplace. Strengths: Best for: AI developers looking to build autonomous agents trained on community-owned or enterprise-specific knowledge bases. Example: Collect a large and diverse dataset of user reviews to train a sentiment analysis AI agent. Website: Core Offering: Decentralized data collection and labeling solution for AI. Strengths: Best For: Enterprises needing diverse, real-world, and structured datasets to train or fine-tune AI models. Example: Collect a 50-language and high-quality dataset for a specialized natural language processing AI. Website: Core offering: Decentralized platform for users to control, monetize, and pool personal data for AI. Strengths: Best for: Building AI models with ethically sourced, user-consented personal data, especially in social, health, and lifestyle domains. Example: Users can leverage Vana to own, control, and monetize their personal data by contributing it to community-led AI projects Website: Core offering: Real-time data network for decentralized data streams. Strengths: Best for: AI systems that rely on live data feeds like autonomous vehicles, smart cities, or trading bots. Example: If your AI business focuses on predicting traffic patterns, you could use Streamr to access real-time data feeds from connected vehicles and sensors. Website: As AI continues to scale, the true bottleneck won't be algorithms—it will be data. Success in the coming wave of AI innovation hinges on timely access to high-quality, well-labeled, and diverse datasets. Yet, efficient data collection infrastructure remains in its infancy. Forward-thinking organizations that invest in scalable, ethical, and AI-ready decentralized data collection solutions now will be the ones leading the industry tomorrow. The age of intelligent data sourcing isn't a trend—it's the next mainstream.
Yahoo
06-03-2025
- Business
- Yahoo
Amazon Leaning More Into AI — 5 Ways It Could Benefit Customers in 2025
AI adoption is a big thing in 2025, with big tech set to spend a quarter trillion dollars on AI systems this year, according to Forbes. Amazon is pouring billions into AI and is set to change how we shop, work and live in 2025. So, how exactly could these AI advancements benefit consumers? Explore More: Find Out: Amazon's AI strategy prioritizes practical applications over speculative tech, with Amazon Web Services (AWS) CEO Adam Selipsky emphasizing a 'customer-obsessed' approach during an interview with The Verge. From AI-curated shopping lists to instant refunds, these upgrades could save households money, time and stress. Here are five ways Amazon's heavy AI investment could directly improve your daily life this year. Amazon's new Nova foundation models, such as the Nova Pro store, Nova Premier store and Nova Reel store, will change the way consumers engage with products. Through Amazon Bedrock, businesses and sellers can leverage such AI solutions in optimizing product listings and ensuring that consumers have quick access to the most relevant possible suggestions. For instance, a search term like 'waterproof hiking backpack for under $100' provides recommendations based on title, customer-made videos and even third-party reviews. The Novas can watch the product video or review it and, via summarized analysis, determine features to highlight or areas to avoid. They can also produce their own videos, showing, for example, how particular furniture would look in your living room. This comes after Amazon invested $4 billion in Anthropic, whose Claude AI models are available for use on Bedrock, the Wall Street Journal reported. Consider This: Currently, Amazon has introduced generative artificial intelligence into its Alexa devices. They can get information about context-aware actions, like adding items to existing lists or adjusting smart home devices on the basis of weather conditions. It also features some guardians and children freedoms, such as question-answer and storytelling for children using Alexa's capabilities. Healthcare integration allows Alexa to make One Medical appointments in exchange for $9 per month, which is half of the normal price. According to Forbes, this comes after the e-commerce giant Amazon bought One Medical, whose vision was to integrate remote and clinic care, for $3.9 billion in early 2022. Rufus is an AI digital assistant developed by Amazon using its own AWS Inferentia chips. It enables user queries for instant returns or refunds. For Prime Day 2024, Amazon used over 80,000 Inferentia/Trainium chips for Rufus to accommodate extremely high traffic. This upgrade has made Amazon Rufus customer service 4.5 times cheaper than its human counterparts. According to Forbes, Rufus reduces customer service costs by up to 45% compared to other support services and has the same level of accuracy. The AI can also provide constant updates on order progress and automatically provide notifications in case of any delay. Amazon One Medical is changing healthcare by embedding artificial intelligence into 1Life, the purpose-built electronic health record system. Created with the help of Amazon's technology teams, 1Life helps to facilitate organizational processes through such methods as recording notes and summing up patients' records. This means that doctors can better concentrate on creating positive interactions with the patient that are not hindered by health information management issues. Some examples of AI-utilizing tools are real-time visit notes, thanks to AWS HealthScribe, and paraphrasing of long patient histories to create relevant care plans. Moreover, an AI messaging system helps the care teams to quickly address the patients' concerns, thus boosting the level of their interaction. These improvements also foster coordination among the care teams to assign work to the most fitting personnel, including doctors and pharmacists. Amazon's AI shopping engine employs real-time price adjustments that surface limited-time discounts based on your browsing history and inventory levels. While Amazon hasn't disclosed specific savings figures, The Wall Street Journal reported that dynamic pricing algorithms are becoming standard across retail, often boosting conversion rates. Retailers using Bedrock can deploy AI-generated video ads showcasing products in realistic scenarios, like testing a raincoat's durability during storms. According to Digitaldefynd, the 'frequently bought together' feature predicts complementary products with high accuracy. Sellers using these tools report 17% higher conversion rates, while shoppers benefit from targeted deals that save the average household $234 annually. More From GOBankingRatesHow Paychecks Would Look in Each State If Trump Dropped Federal Income Tax5 Cities You Need To Consider If You're Retiring in 2025 This article originally appeared on Amazon Leaning More Into AI — 5 Ways It Could Benefit Customers in 2025
