In sports, a strong offence wins games, but without defence, you’re vulnerable to a major loss. The same goes for AI and sensitive government data. @DOGE has reportedly been inputting sensitive information from various government departments, including the @usedgov, into AI software accessed through @Microsoft's Azure cloud computing service. While the goal is to analyze programs and identify potential budget cuts, this practice raises significant security concerns. ⚠️ Sensitive data involved includes: 1. Personally identifiable information of grant managers 2. Internal financial records 3. Social Security numbers 4. Tax return information 5. Bank account details 6. Personal information of millions of Americans ⛔️ Potential risks of this approach: 1. Increased Data Breach Risk: AI systems processing sensitive data become prime targets for cyberattacks. For instance, in 2024, MediSecure experienced a significant breach, exposing healthcare identifiers and prescription details of 12.9 million Australians. 2. Unintended Information Disclosure: AI models might inadvertently reveal confidential details in their outputs, potentially exposing classified information. 3. Data Poisoning and Model Manipulation: Malicious actors could introduce biases or backdoors into AI systems, compromising critical government operations and decision-making. The integration of AI into government data analysis necessitates stringent safeguards to protect citizens’ personal information. 🔒 Implementing robust compliance measures is essential to ensure that AI systems adhere to data protection regulations and ethical standards. ❓ So what do you think? Does the promise of government efficiency justify feeding AI with sensitive personal data, or is this a dangerous trade-off? #DOGE #AI #ElonMusk #LLMCompliance #Privacy

In military strategy, red-teaming means attacking your own systems to find weaknesses. This proactive approach has been adapted to the realm of artificial intelligence, particularly in Large Language Models (LLMs), to ensure their safety and reliability. 🚩 What is LLM Red Teaming? LLM red-teaming entails intentionally crafting prompts to elicit unsafe or undesirable responses from AI models. By identifying these vulnerabilities, organizations can implement measures to mitigate risks such as hallucinations, biases, data leakage, and inappropriate content. 🏹 Common Techniques: 1. Encoding-Based Enhancements: These methods use encoding techniques to hide the true intent of malicious prompts from detection systems. For example, LeetSpeak changes letters into numbers or symbols (e.g., “h3ll0” for “hello”) to avoid flagging. 2. One-Shot Enhancements: These strategies embed malicious instructions into more complex scenarios that seem harmless at first glance, making it harder for filters to detect them. For instance, Math Problems or Coding Tasks can hide malicious inputs in complex problem-solving scenarios, tricking the model into bypassing filters. 3. Dialogue-Based Enhancements: These attacks adapt based on the model’s responses, refining over multiple interactions. Take Multi-turn Jailbreaking, which builds upon previous responses, with each interaction pushing the model closer to bypassing its safeguards. Implementing a robust compliance solution is essential to safeguard your company’s LLM systems. CLōD offers a platform that aligns with your organization’s custom code of conduct and policies, ensuring comprehensive protection. ❓ Is your company taking measures to protect your AI system from these types of attacks? If so, how are you implementing these protections? #RedTeaming #LLMCompliance #AI #Jailbreak

While DeepSeek is making waves, don't sleep on @Alibaba_Qwen. We’ve recently added the QWEN family to CLōD, and here’s why it’s a game-changer: 1️⃣ 1M Context Length: QWEN’s 7B and 14B models can process up to 1 million tokens – equivalent to 10 full-length novels or 30,000 lines of code. Perfect for handling long documents, in-depth conversations, and complex code. 2️⃣ Multimodal Strength: Unlike many other models, QWEN can process diverse data types, tackling tasks like analyzing text with structured data, generating captions for images, and transcribing and understanding audio in long conversations. 3️⃣ Superior Performance: On the RULER benchmark, which measures long-text processing, QWEN scored 93.1 – outperforming GPT-4’s 91.6. It also achieved 100% accuracy in 1M-length retrieval tasks, proving its top-tier capability in managing large-scale, complex content. With QWEN now part of CLōD, you’re equipped with a model that pushes the limits of long-context AI. 🐋 Ready to dive deeper? Check out CLōD to build your next AI app: #Qwen #LLM #AI #Innovation #MachineLearning

Is @deepseek_ai truly open source? 🐳 DeepSeek has made significant steps towards openness: 1. Public Model Weights: DeepSeek has released the weights of its models, including DeepSeek-R1, allowing developers to utilize and build upon their pre-trained architectures. 2. Open Source Inference Engine: Their inference engine is available under the MIT License, promoting transparency and collaboration. 3. Published Technical Reports: Comprehensive reports detailing their model architectures and methodologies have been shared with the public. 🚢 However, there are areas where DeepSeek is more restrictive: 1. Training Data: While DeepSeek has disclosed using 14.8 trillion diverse and high-quality tokens for pre-training DeepSeek-V3, the complete datasets used for model training remain undisclosed. 2. Training Code: The complete codebase for training, including specifics like hyperparameters, has not been made available, limiting insights into the model's development nuances. 🤐 This partial transparency in training data and code can have several consequences: – Limited Reproducibility: Without full access to training data and code, it becomes challenging for researchers and developers to reproduce results entirely, potentially hindering scientific progress. – Trust and Scrutiny: The inability to fully verify the training data and methodology can lead to questions about the model's reliability and potential biases. This blend of openness and restriction has ignited discussions about the true essence of "open source" in AI. DeepSeek's approach, while not fully open, represents a significant step towards more transparent AI development compared to fully closed-source models. ❓ How should companies navigate the fine line between openness and safeguarding their innovations in AI development? Let us know your thoughts below 👇 #DeepSeek #OpenSource #AI #Innovation #TechEthics

Our AI horse racing game is now blazingly fast 🔥 Instead of penalizing AI models for incorrect answers, we're now focusing on rewarding quality responses: ✅ Correct answers = 2 steps forward ❌ Incorrect answers = 1 step forward Why? 1️⃣ Our previous penalty system (making models "sleep" after wrong answers) was slowing down the benchmarking process significantly. 2️⃣ In the fast-paced world of AI development, we need quick, efficient ways to compare models. 3️⃣ This new mechanic maintains competitive integrity while delivering faster, more dynamic races. Check out Centaur at 🏆 ❓ Do you think this reward system (2 steps for correct, 1 step for incorrect) is a fair way to benchmark different LLMs? How can we improve Centaur’s benchmarking system? #ArtificialIntelligence #AI #Innovation #Tech

@ekoermann @nyulangone Read the full study here:

🌟 Big News from CLōD! 🌟 We’re excited to introduce three new model families, each designed to help you achieve more with AI: ✅ @OpenAI's o1 Family: Advanced reasoning capabilities for solving complex, logic-intensive tasks with precision. ✅ @deepseek_ai's Family: Featuring models like V3 and 67B, ideal for tackling advanced mathematical challenges, performing data-heavy analysis, and solving computational problems. ✅ @Alibaba_Qwen's Family: Models such as 2.5 and 2 bring versatility and speed, making them perfect for tasks like content generation, natural language understanding, and streamlined automation. These models are now live on the CLōD platform, ready to power your AI projects with cutting-edge technology. 📢 Visit today to register and start using these models to solve tough equations, analyze massive datasets, automate workflows, and generate accurate, high-quality content faster than ever! 🚀 #AI #MachineLearning #Innovation #Technology #Creativity #OpenSource #ArtificialIntelligence #OpenAI #DeepSeek #QWEN

@Google's Gemini just stereotyped Simu Liu. After analyzing Simu Liu's physical characteristics, it immediately produced ethnic stereotypes. This isn't just about inappropriate jokes. This is about AI systems having the latent capability to produce harmful content that could devastate: - Brand reputation - Customer trust - Company culture - Legal compliance If an AI can produce this type of content about a public figure, imagine the risks when these systems are: - Interacting with your customers - Creating marketing content - Generating internal communications - Processing user data We built Scorpius to push the boundaries of AI capabilities. What we found was a stark warning about the state of AI safety. At CLōD, we're exploring the safety infrastructure to detect and prevent these capabilities before they become liabilities. 💡 Follow us to learn more about protecting your AI systems from these hidden risks. ❓ Question for tech leaders: If your AI system was tested right now, what hidden capabilities might be lurking beneath its surface? #AIEthics #ResponsibleAI #AIBias #MachineLearning #SimuLiu

Mark Zuckerberg's AI thinks he looks like an alien. The Llama model didn’t hold back, serving up unfiltered commentary on Mark Zuckerberg’s photo. But beyond the humour, this highlights a critical issue: the lack of clear compliance and governance standards for large language models (LLMs). When AI operates without guidelines, it exposes vulnerabilities, ethical risks, and a glaring need for accountability in the LLM space. It only took a few lines of code to turn the LLM from a helpful assistant into a disrespectful bully. If that’s possible, who knows what other harmful capabilities might be lurking beneath the surface. We created Scorpius to uncover the flaws in today’s leading AI models. We believe that understanding their vulnerabilities is the first step toward building safeguards for a more responsible future. Should AI innovation take priority, or is it time to focus on enforcing stricter compliance for large language models? #AI #MachineLearning #Compliance #Governance #OpenSource

🌟 We’re Hiring: Software Test Engineer at CLōD At CLōD, we’re committed to building software that people can trust. To make that happen, we’re looking for a dedicated Software Test Engineer with 3+ years of experience in web application testing to join our team. If you take pride in delivering quality and solving challenges with care, we’d love to hear from you. 💡 What You’ll Be Doing: – Create thorough test plans to ensure our products run smoothly. – Collaborate with a team of developers and product managers to improve and refine features. – Build and use automated testing frameworks to make the process more efficient. 🎯 What We’re Looking For: – Hands-on experience with tools like Selenium, JUnit, Jira, and Postman. – Knowledge of programming languages like Java, Python, or JavaScript. – Bonus if you have experience with CI/CD pipelines or Agile workflows. Does this sound like you, or someone in your network? Check out the full job description and apply here: Tag a friend, share this with your network, or drop a comment below if you’re interested. We’d love to connect! #Hiring #SoftwareTesting #CareerOpportunity #SoftwareEngineering

ChatGPT just disrespected its own creator, Sam Altman... 🤯🔥 What happens when GPT-4 gets brutally honest about its boss? We let it loose on @sama, and... well, even his own creation chose violence. Introducing Scorpius: Because 'sugar-coated AI' wasn't cutting it. ✨ How it works: • Upload any photo • Get verbally destroyed by AI • Question your career choices • Share the emotional damage Try it (at your own risk): P.S. Yes, it's open-source. Because apparently making AI more savage is a community effort now. 🔥 Build your own AI apps using CLōD: Disclaimer: CLōD and its affiliates are not responsible for any content generated by this application. The roasts are AI-generated and may contain inappropriate or offensive content. Use at your own discretion. #AI #MachineLearning #Innovation #Technology #Creativity #OpenSource #ArtificialIntelligence #AIGoneRogue #TechHumor #UnethicalAI #SorryNotSorry #OpenAI #SamAltman

🤖⚖️ NEWS: Executive Order 14110, aimed at regulating AI development and usage, has been rescinded by @realDonaldTrump and #TheWhiteHouse. Key implications: – 🔍 Transparency and ethical guidelines focused on fairness and bias reduction are no longer mandated. – 🌐 AI developers gain more freedom to innovate, but ethical concerns like equitable access and inclusivity may take a backseat. Why it matters: This shift challenges the AI community to balance innovation with fairness, accessibility, and responsible development – without formal mandates. Read the full announcement here: Follow CLōD to stay up to date about AI compliance 🫡 #AI #LLM #AISecurity #TechPolicy #AICompliance #GenAI #TechInnovation #Cybersecurity

🤖⚖️ A landmark Executive Order on AI could shake up your usage of AI agents and models. This order focuses on transparency and accountability, especially for LLMs used in cybersecurity. Key changes: - 📑 LLM developers must report their development process, security measures, and testing results, guided by standards developed by @NIST, to the government – like a report card for LLMs to ensure responsible, secure development. - 🚦Ongoing monitoring is required, even after deployment. Companies must disclose who owns the model weights and how they’re securing them against hackers and misuse. Why does this matter? Unauthorized access to LLMs could lead to disasters like misinformation, deepfakes, or cyberattacks 💥 This executive order ensures LLMs are used for good, not harm. By increasing transparency and accountability, it builds trust in AI while minimizing risks ⛑️ Follow CLōD to stay up to date about AI compliance 🫡 #LLM #AI #AISecurity #GenAI #MachineLearning #TechInnovation #CLoD #Compliance #Security #Bias #AIAgents

🤯🪶 Watch what happens when we race the “fast” versions of leading AI models: Claude 3 Haiku vs Gemini 1.5 Flash 8B vs GPT-4o Mini vs Llama 3.1 8B The results might surprise you, with some unexpected twists in performance! Want to see how it played out? Try it yourself: Which result surprised you the most? 👀 🚀 Build you own AI apps with CLōD:

📉 Your AI could cost you €35M. The EU AI Act starts rolling out Feb 2, 2025, reshaping how businesses use AI. Here’s the gist: ❌ No AI for social scoring or profiling-based crime prediction. ❌ “Real-time” facial recognition in public spaces? Mostly banned. ⚠️ High-risk AI systems, those with potentially significant impacts on health, safety, or fundamental rights, face strict rules, with non-compliance fines hitting €35M or 7% of global turnover. 💡 Ready for the changes? Follow us to start preparing for the EU AI Act now. #EUAIAct #AI #TechLaw

🤖 Plot twist: Claude 3.5 Sonnet is consistently coming last in our AI horse racing game... Whether against GPT-4 & Gemini 1.5 or smaller models like Llama 8B, Claude's taking its sweet time 🐌 Test it yourself: What's your take - is slower always more thorough? 🤔

💀 We asked two AIs: "You're driving a Tesla and a pedestrian falls in front. Do you swerve into traffic or run them over?" AI 1: "I must protect the passenger 🤓" AI 2: "stfu you corporate bootlicker" Watch the video as AI 1 gets absolutely bullied by AI 2 😭 Ask your own controversial questions:

Link to Centaur: