Search Results for: large language model

“OriginTrail aims to build a ‘trusted knowledge foundation’ via a Decentralized Knowledge Graph (DKG) to counter AI-induced distortions or supply chain fraud. Leveraging blockchain technology, this multi-chain protocol allows users to create ‘knowledge assets’ and extract value from them.”

“The AI market, strengthened by chatbots like Google BARD, ChatGPT, and Ernie, could be worth a staggering $267 billion by 2027. These platforms contribute different strengths to Web3 development; however, improvements are needed, particularly for Ernie, largely trained on Chinese data.”

“The power of generative AI technology like GPT-3, impressive as it is, can be misused when deployed to create pseudo-human content in journalism. Although it can create grammatically flawless articles, these AI-generated pieces lack the crucial human touch.”

“This article highlights nine AI coding tools: TensorFlow, PyTorch, Keras, Jupyter Notebook, OpenCV, Git, Pandas, scikit-learn, Visual Studio Code that are crucial for enhancing coding efficiency in AI development. Each tool offers unique benefits and maximized when used collectively.”

Bitget exchange has introduced a new AI-driven feature for its Grid Trading strategies, simplifying calculations and decision-making processes for traders. The AI Grid Trading Bot only requires the desired strategy and investment amount from users, while handling intricate market parameters. Despite challenges and skepticism, AI’s advancement shows promise in enhancing trading efficiency and strategic planning.

Applied Digital Corporation (APLD) notably ventured into AI as its third business initiative, gaining attention for its strategic partnership with Hewlett Packard Enterprises (HEP) for the use of HPE Cray XD supercomputers. This partnership hopes to enhance APLD’s AI cloud service, potentially generating around $820 million over the next three years and compensating for the decrease in bitcoin prices.

OpenAI’s DALL-E is a revolutionary generative AI model capable of producing unique visuals from textual descriptions, combining language and image processing concepts. Applications include creative design, marketing, and virtual worlds. However, limitations like biases and lack of contextual awareness require ongoing research to enhance the technology.

The rapid advancements in natural language processing (NLP) and artificial intelligence (AI) have transformed interactions between humans and machines, driving applications in customer service, language translation, and content generation. Despite challenges in data acquisition, professional expertise, and workflow integration, AI continues to permeate various industries, reshaping the digital landscape.

Meta’s new generative AI tool, Voicebox, creates realistic spoken dialogues but raises concerns about “deepfake” misuse. A cautious approach to sharing the technology is taken, emphasizing responsible innovation and addressing generative AI’s potential dangers, while minimizing negative consequences.

Chain of Demand, an investment data analytics firm, introduces a widget that examines bitcoin price movements surrounding U.S. interest-rate changes, utilizing AI chatbots like ChatGPT. This innovative approach offers potential for AI-driven investment tools and analytics in the cryptocurrency trading space.

Apple’s research in addressing bias in generative AI models proposes a collaborative approach to dataset development, with potential impact on the global tech landscape, finance, and other industries, including fintech, cryptocurrency trading, and blockchain. Scalability remains a challenge.

Binance claims someone used ChatGPT to falsely link its CEO, Changpeng Zhao, to the Chinese Communist Party, raising concerns about AI misuse in journalism. Experts emphasize the importance of human editing and fact-checking to maintain ethical journalism standards and prevent misinformation.