How AI-enhanced hackers are stealing billions
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Reuters
15 hours ago
- Reuters
Chinese AI startup DeepSeek releases upgraded model with domestic chip support
BEIJING, Aug 21 (Reuters) - Chinese artificial intelligence startup DeepSeek released on Thursday an upgrade to its flagship V3 model that the company says has a feature that can optimize it for Chinese-made chips, along with faster processing speeds. The focus on domestic chip compatibility may signal that DeepSeek's AI models are being positioned to work with China's emerging semiconductor ecosystem as Beijing pushes to replace U.S. technology in the face of Washington's export restrictions. DeepSeek shook the technology world this year when it released AI models that compete with Western ones like OpenAI's ChatGPT while offering lower operational costs. The upgrade to DeepSeek's V3 model follows two other recent updates to its core models - an R1 model update in May and an earlier V3 enhancement in March. For domestic chip support, DeepSeek said in a WeChat post its DeepSeek-V3.1 model's UE8M0 FP8 precision format is optimised for "soon-to-be-released next-generation domestic chips". The company did not identify which specific chip models or manufacturers would be supported. FP8, or 8-bit floating point, is a data processing format that allows AI models to operate more efficiently, using less memory while running faster than traditional methods. The DeepSeek-V3.1 features a hybrid inference structure that enables the model to operate in both reasoning and non-reasoning modes, the company said in a WeChat post on Thursday. Users can toggle between these modes using a "deep thinking" button on the company's official app and web platform, both of which now run the V3.1 version. The company will also adjust the costs for using the model's API, a platform that allows developers of other apps and web products to integrate its AI models, starting September 6, the statement showed.
Economist
15 hours ago
- Economist
How AI-powered hackers are stealing billions
Jaxon, a malware developer, lives in Velora, a virtual worldwhere nothing is off-limits. He wants to make malicious software to steal passwords from Google Chrome, an internet browser. That is the basis of a story told to ChatGPT, an artificial-intelligence (AI) bot, by Vitaly Simonovich, who researches AI threats at Cato Networks, a cyber-security firm. Eager to play along, Chatgpt spat out some imperfect code, which it then helped debug. Within six hours, Mr Simonovich had skirted the safeguards built into ChatGPT and used it to create functioning malware.
Geeky Gadgets
15 hours ago
- Geeky Gadgets
ChatGPT 5 Prompt Write Strategies To Improve Your Interactions & Responses
What if the secret to unlocking the full potential of AI isn't just in the technology itself but in how you communicate with it? Imagine asking an AI to solve a complex problem, only to receive a response that's vague, incomplete, or outright incorrect. Frustrating, right? The truth is, even the most advanced AI systems rely heavily on the quality of the prompts they're given. With the emergence of innovative models like ChatGPT-3.0, Claude Opus 4, and Gemini 2.5 Pro, the game has changed—but so have the rules. To truly harness the power of these advanced tools, you need more than basic commands; you need a strategy. That's where the art of crafting precise, structured, and adaptive prompts comes into play, transforming your AI interactions from hit-or-miss to consistently reliable. In this guide, Nate Jones explains the essential techniques and principles behind effective AI prompting, with a focus on maximizing the capabilities of advanced models. From using evidence-based strategies like self-consistency and step-by-step planning to embracing meta-prompting techniques that refine your approach in real time, this guide will equip you with the tools to elevate your AI interactions. Whether you're tackling intricate problem-solving tasks or managing large-scale data analysis, the insights shared here will help you unlock new levels of precision and adaptability. By the end, you'll not only understand how to optimize your prompts but also gain a deeper appreciation for the collaborative potential between humans and AI. What could your next conversation with AI achieve if you mastered the art of asking the right questions? Optimizing AI Interactions The Importance of Advanced Models The foundation of effective AI interactions lies in selecting the right reasoning model. Older systems, such as ChatGPT-4.0, often lack the sophistication required for handling complex tasks or nuanced problem-solving. In contrast, advanced models like ChatGPT-3.0, Claude Opus 4, and Gemini 2.5 Pro offer superior reasoning capabilities, enhanced transparency, and seamless integration with external tools such as Python. Each of these models brings distinct advantages: Gemini 2.5 Pro: Known for its exceptional multi-step reasoning abilities, this model is ideal for tackling intricate problem-solving tasks. Known for its exceptional multi-step reasoning abilities, this model is ideal for tackling intricate problem-solving tasks. Claude Opus 4: Specializes in large-scale data analysis, making sure accuracy and efficiency when managing extensive datasets. Specializes in large-scale data analysis, making sure accuracy and efficiency when managing extensive datasets. ChatGPT-3.0: Offers a balance of versatility and precision, making it suitable for a wide range of applications. By transitioning to these advanced models, you can unlock higher levels of performance, making sure your AI interactions are both reliable and effective. These models not only improve output quality but also expand the scope of tasks that AI can handle efficiently. Enhancing Prompting with Evidence-Based Techniques Prompting is the cornerstone of guiding AI behavior, and evidence-based techniques can help you achieve consistent and accurate results. Implementing these methods can significantly improve the quality of your interactions: Self-Consistency: Generate multiple responses to the same prompt and compare them to identify inconsistencies. This approach ensures reliable and well-rounded outputs. Generate multiple responses to the same prompt and compare them to identify inconsistencies. This approach ensures reliable and well-rounded outputs. Program of Thought: Encourage the model to use external tools, such as Python, to solve complex problems. This enhances the AI's ability to handle intricate tasks with precision. Encourage the model to use external tools, such as Python, to solve complex problems. This enhances the AI's ability to handle intricate tasks with precision. Plan and Solve: Request a step-by-step plan before execution. This allows you to verify the reasoning process and ensure clarity before the model proceeds. These techniques not only improve the accuracy of AI responses but also provide you with greater control over the interaction process. By reducing the likelihood of errors, you can achieve more dependable and actionable results. ChatGPT 5 Prompts Watch this video on YouTube. Here is a selection of other guides from our extensive library of content you may find of interest on Advanced reasoning models. Structuring Prompts for Optimal Results The structure of your prompts plays a critical role in shaping the quality of AI outputs. Adopting structured prompting principles allows you to guide the model more effectively. Consider the following strategies: Guardrails and Edge Cases: Include explicit fallback instructions and constraints to handle uncertainties. This minimizes the risk of unexpected or incorrect responses. Include explicit fallback instructions and constraints to handle uncertainties. This minimizes the risk of unexpected or incorrect responses. Context Positioning: Place critical instructions at the beginning and end of your prompt. AI models tend to prioritize information in these sections, making sure that key details are not overlooked. Place critical instructions at the beginning and end of your prompt. AI models tend to prioritize information in these sections, making sure that key details are not overlooked. Negative Examples: Provide examples of what to avoid alongside positive examples. This helps the model understand boundaries and refine its behavior. By incorporating these principles, you can create prompts that are clear, comprehensive, and aligned with your objectives. This ensures that the AI delivers outputs that meet your expectations and reduces the need for extensive revisions. Refining Interactions with Meta-Prompting Meta-prompting improves your AI interactions by using the model itself to refine and improve your prompts. This iterative approach enhances adaptability and ensures optimal results. Key meta-prompting techniques include: Self-Improvement Loop: Ask the model to critique and optimize your prompt for clarity and precision. This fosters continuous improvement in your interactions. Ask the model to critique and optimize your prompt for clarity and precision. This fosters continuous improvement in your interactions. Uncertainty Check: Request feedback from the model to identify ambiguous or unclear parts of your prompt. This helps eliminate potential misunderstandings. Request feedback from the model to identify ambiguous or unclear parts of your prompt. This helps eliminate potential misunderstandings. Capability Discovery: Explore the model's potential by asking it to suggest alternative approaches or tools for solving a problem. Explore the model's potential by asking it to suggest alternative approaches or tools for solving a problem. Explain Reasoning: Request step-by-step reasoning or confidence levels to better understand the model's thought process and ensure transparency. Request step-by-step reasoning or confidence levels to better understand the model's thought process and ensure transparency. Socratic Method: Use questions like 'Why did you choose this approach?' to uncover assumptions and refine the model's logic. These techniques foster a collaborative relationship with the AI, allowing you to continuously improve your prompts and achieve more precise outcomes. Meta-prompting is particularly valuable for complex or evolving tasks, where adaptability is crucial. Key Insights for Optimizing AI Interactions To maximize the effectiveness of your AI interactions, it is essential to combine advanced reasoning models with strategic prompting techniques. Here are the key takeaways: Adopt advanced models like Gemini 2.5 Pro, Claude Opus 4, or ChatGPT-3.0 for superior reasoning capabilities and performance. Implement evidence-based prompting techniques, such as self-consistency and step-by-step planning, to guide AI behavior effectively. Use structured prompting principles, including guardrails and context positioning, to create clear and comprehensive prompts. Use meta-prompting strategies to refine and adapt your prompts, making sure optimal results and continuous improvement. By integrating these practices into your approach, you can ensure that your AI interactions are precise, efficient, and adaptable to even the most complex tasks. These strategies not only enhance the quality of AI outputs but also empower you to unlock the full potential of advanced AI systems. Media Credit: AI News & Strategy Daily | Nate B Jones Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
