Latest news with #AmazonWebService
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.
23-04-2025
- Business
Japan PM Ishiba Meets with Amazon Executive
News from Japan Politics Technology Apr 23, 2025 13:45 (JST) Tokyo, April 23 (Jiji Press)--Japanese Prime Minister Shigeru Ishiba met with Matt Garman, CEO of Amazon Web Service (AWS) Inc., the cloud arm of U.S. e-commerce giant Inc., at the prime minister's office in Tokyo on Wednesday. During the meeting, Ishiba said, "Japan's problem is that its population is decreasing at a frightening pace," "Technology plays a crucial role in solving the most important issue of our country," the prime minister also said, showing his hope for stronger cooperation with AWS. Garman explained AWS's plans to increase investment in Japan and said that the company wants to support the Japanese economy. END [Copyright The Jiji Press, Ltd.] Jiji Press
Korea Herald
04-03-2025
- Business
- Korea Herald
LG CNS, AWS launch task force to support enterprise AI integration
LG CNS said Tuesday it has established a task force in collaboration with Amazon Web Service to support companies facing technological, cost and time constraints in adopting generation AI services. The AWS-LG CNS GenAI Launch Center aims to develop 100 enterprise-level generative AI services rapidly and cost-effectively. LG CNS has secured multiple AI transformation projects in the financial sector, including banking, insurance, securities and credit card services, while expanding its presence in manufacturing. The company also obtained AWS generative AI competency certifications last year. Through the new center, business clients will be able to implement solutions such as customized chatbots, marketing content and image generation services, and issue summarization and response platforms. To enhance the speed of generative AI service development, LG CNS will leverage its proprietary AI solutions, allowing seamless AI integration into existing enterprise applications. Moreover, LG CNS and AWS will strengthen their synergy in generative AI services. Through Amazon Bedrock, a managed service that provides access to major AI foundation models, clients will be able to select the most suitable AI model for their needs. In addition to AWS' next-generation foundation model Amazon Nova, companies will also gain access to AWS' high-performance computing hardware. 'Through our collaboration with AWS, we will lower the barriers for all domestic enterprises to adopt generative AI. Both companies will actively pursue joint generative AI business initiatives and expand into the Asia-Pacific and Japan markets,' said LG CNS CEO Hyun Shin-gyoon.
Korea Herald
06-02-2025
- Business
- Korea Herald
LG CNS posts record profit in 2024
Korean IT solutions provider LG CNS said Thursday it achieved record-high yearly sales of 5.9 trillion won ($4.07 billion) in 2024, backed by robust sales in cloud and artificial intelligence business. Operating profit for the year stood at 512.9 billion won, growing 10.5 percent on-year, while annual sales increased 6.2 percent on-year. For the October-December period, LG CNS also posted best quarterly sales of 2.02 trillion won, up 6.2 percent on-year. The operating profit also increased 1.1 percent on-year to stand at 2 billion won. LG CNS attributed the growth in sales to its cloud and AI service business, which grew 15.8 percent on-year. According to the company, cloud and AI business took 56 percent of the annual sales, posting 3.3 trillion won. In the cloud sector, LG CNS has established a leading position as a managed service provider, and has built strong partnerships with global cloud service providers, such as Amazon Web Service and Google Cloud. The IT company was the first in Korea to achieve the AWS Generative AI Competency qualification from AWS last June. In October, the company became the first in Asia to secure Google Cloud's Generative AI Service Specialization certificate. LG CNS is also actively expanding its presence in the AI sector, launching DAP GenAI, a generative AI service platform helping corporate customers in developing their own AI models, and DRAG, which is a generative AI model for images based on multimodal capabilities. As a new growth driver, the company is also ramping up investment in AI data center business. LG CNS is working together with the Korea Institute of Energy Technology Evaluation and Planning for joint research on immersion cooling technology. The company is also planning to introduce a monitoring system for equipment overheating using digital twin technology. LG CNS made its stock market debut on the nation's main bourse Kospi on Wednesday, with its stock ending trading at 55,800, down 9.85 percent from its IPO price of 61,900 won. On Thursday, the stock was trading at 56,400 as of 2:30 p.m.
