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Unveiling the MailerLite Phishing Attack: A Deep Dive into the Crypto Market Breach

The recent phishing attack on email service provider MailerLite has raised significant concerns within the crypto market. The company disclosed to Decrypt that the breach, which occurred when a support team member unwittingly fell victim to a deceptive link and provided their Google credentials, resulted in unauthorized access to MailerLite's internal system. Here are the key points of the incident: Hackers gained access to MailerLite's internal system by executing a password reset for a specific user on the admin panel. They were able to impersonate user accounts, focusing primarily on cryptocurrency-related accounts. A total of 117 accounts were accessed, with some being used to launch phishing campaigns using stolen information. Notable affected accounts included CoinTelegraph, Wallet Connect, Token Terminal, DeFi, and Decrypt. The hackers managed to steal over $580,000, according to ZachXBT, with the funds being sent to a specified address. Web3 security firm Blockai

# Nvidia's Eureka: A Breakthrough in Robotic Dexterity Using AI and Language Models

use of generative AI and reinforcement learning allows robots to learn complex tasks through trial and error, surpassing the effectiveness of human-authored programs. This breakthrough in robotic dexterity holds great promise for the future of AI and robotics.

Eureka's ability to teach robots complex skills like pen spinning tricks and other tasks showcases the power of Nvidia's pioneering work in steering AI with language models. By leveraging the advancements in large language models, such as OpenAI's GPT-4, Eureka autonomously writes sophisticated reward algorithms that enable robots to learn through trial and error reinforcement learning. This approach has proven to be over 50% more effective than human-authored programs, as outlined in the paper published by Nvidia.

Notably, Eureka has successfully taught various types of robots, including quadrupeds, dexterous hands, and cobot arms, to perform tasks such as opening drawers, using scissors, and catching balls. The versatility of Eureka's teaching capabilities demonstrates its potential in enhancing the dexterity and adaptability of robots across different industries.

Furthermore, Nvidia's commitment to advancing the field of AI is evident through their recent open sourcing of SteerLM, a method that aligns AI assistants to be more helpful by training them on human feedback. Similar to Eureka, SteerLM utilizes language models to improve AI assistant alignment. By having AI assistants practice conversations and receive feedback on attributes like helpfulness, humor, and quality, SteerLM enables them to provide tailored responses to users' needs. This iterative learning approach enables AI to become more beneficial for real-world applications.

The common thread in Nvidia's work is the utilization of advanced neural networks in innovative ways, both in hardware and software. Whether it is teaching robots complex skills or training AI assistants to be more helpful, Nvidia's research and development efforts are pushing the boundaries of what AI and robotics can achieve. The breakthrough achieved by Eureka in robotic dexterity is a testament to Nvidia's commitment to advancing AI technology.

In summary, Nvidia's Eureka AI agent represents a major leap in robotic dexterity. By leveraging generative AI and reinforcement learning, Eureka has successfully taught robots complex skills, surpassing the effectiveness of human-authored programs. This breakthrough, along with Nvidia's other advancements in AI assistant alignment, showcases their commitment to pushing the boundaries of AI and robotics. The future implications of Eureka's capabilities in enhancing the dexterity and adaptability of robots are exciting, and Nvidia's pioneering work continues to drive progress in the field of AI.

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