The hottest AI safety Substack posts right now

And their main takeaways
Category
Top Technology Topics
ChinaTalk 370 implied HN points 20 Nov 24
  1. AI Safety Institutes, or AISIs, are new groups set up to focus on the safety of advanced artificial intelligence. They help create guidelines and conduct research.
  2. China has not yet created an official AI Safety Institute, which raises questions about its role in global AI safety discussions. Some believe it should establish one to formally participate in international efforts.
  3. Despite not having an AISI, several Chinese organizations already work on AI safety, but this makes coordination and engagement with international partners more complex.
Am I Stronger Yet? 172 implied HN points 20 Nov 24
  1. There is a lot of debate about how quickly AI will impact our lives, with some experts feeling it will change things rapidly while others think it will take decades. This difference in opinion affects policy discussions about AI.
  2. Many people worry about potential risks from powerful AI, like it possibly causing disasters without warning. Others argue we should wait for real evidence of these risks before acting.
  3. The question of whether AI can be developed safely often depends on whether countries can work together effectively. If countries don't cooperate, they might rush to develop AI, which could increase global risks.
The Intrinsic Perspective 8431 implied HN points 23 Mar 23
  1. ChatGPT's capabilities include suggesting design for disturbing scenarios like a death camp.
  2. Remote work is associated with a recent increase in fertility rates, contributing to a fertility boom.
  3. The Orthogonality Thesis within AI safety debates highlights the potential risks posed by superintelligent AI's actions.
Astral Codex Ten 2271 implied HN points 19 Feb 24
  1. ACX provides an open thread for weekly discussions where users can post anything, ask questions, and engage in various topics.
  2. ACX Grants project includes initiatives like exploring a mutation to turn off suffering and opportunities for researchers in AI safety.
  3. ACX mentions upcoming events like a book review contest with updated rules and a pushed back due date.
Resilient Cyber 19 implied HN points 04 Sep 24
  1. MITRE's ATLAS helps organizations understand the risks associated with AI and machine learning systems. It provides a detailed look at what attackers might do and how to counteract those strategies.
  2. The ATLAS framework includes various tactics and techniques that cover the entire lifecycle of an attack, from reconnaissance to execution and beyond. This helps businesses prepare better defenses against potential threats.
  3. Using tools like ATLAS and its companion resources can help secure AI adoption and development by highlighting vulnerabilities and suggesting mitigations to reduce risks.
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Thicket Forte 819 implied HN points 02 Apr 23
  1. People are frustrated with the beliefs and ideas of Eliezer Yudkowsky. They feel overwhelmed by the impact his views have had on their lives. It's exhausting to navigate the complicated discussions around AI safety.
  2. Yudkowsky's warnings about AI risks seem to have attracted more interest in AI instead of preventing problems. Some believe his approach only made things worse, which feels ironic to his followers.
  3. There's a sense that relying on one person's ideas, like Yudkowsky's, isn't enough to solve complex issues. Collaboration and collective thinking are seen as necessary to address the challenges of AI effectively.
Import AI 299 implied HN points 12 Jun 23
  1. Facebook used human feedback to train its language model, BlenderBot 3x, leading to better and safer responses than its predecessor
  2. Cohere's research shows that training AI systems with specific techniques can make them easier to miniaturize, which can reduce memory requirements and latency
  3. A new organization called Apollo Research aims to develop evaluations for unsafe AI behaviors, helping improve the safety of AI companies through research into AI interpretability
Artificial Ignorance 130 implied HN points 06 Mar 24
  1. Claude 3 introduces three new model sizes; Opus, Sonnet, and Haiku, with enhanced capabilities and multi-modal features.
  2. Claude 3 boasts impressive benchmarks with strengths like vision capabilities, multi-lingual support, and operational speed improvements.
  3. Safety and helpfulness were major focus areas for Claude 3, addressing concerns like reducing refusals while balancing between answering most harmless requests and refusing genuinely harmful prompts.
Asimov’s Addendum 2 HN points 04 Sep 24
  1. AI safety discussions should focus not only on stopping outside threats but also on the risks from the owners of AI systems. These owners can create harm while just trying to achieve their business goals.
  2. There is a need to recognize and learn from past technology failures as these patterns might repeat with AI. We should not overlook potential issues that arise from how AI is managed and used.
  3. It's important for AI developers to share what they are measuring and managing in terms of safety. This information can help shape regulations and improve safety practices as AI becomes more integrated into business models.
Breaking Smart 90 implied HN points 16 Dec 23
  1. A new program called Summer of Protocols has produced a wealth of research output focused on the study of protocols and hardness in technology and the world at large.
  2. The Protocol Kit from the Summer of Protocols is a free publication containing essays, artwork, and tools to spark interest and discussion around protocols.
  3. Thinking in terms of 'hardness' and 'protocols' can be a powerful approach for various fields, from technology to party planning, providing a new perspective on problem-solving and creativity.
Philosophy bear 92 implied HN points 24 Nov 23
  1. AI safety could become a left-wing issue, with corporations unlikely to sustain alliances with safety proponents in the long run.
  2. There may be a split within Effective Altruism due to relationships with corporations, leading to a 'left' and 'right' division.
  3. The AI safety field might divide into accommodationist and regulation-leaning factions, reflecting broader political trends.
world spirit sock stack 3 implied HN points 11 Nov 24
  1. Winning is not always about immediate power; it's about the real outcomes that come afterward. Sometimes, what seems like a win can lead to a bigger loss for everyone involved.
  2. When people want the same ultimate outcome, like a better future with AI, it’s better to focus on who is making the right choices rather than who has the most power.
  3. If one side pushes for something without considering reality, they might end up hurting everyone, including themselves. True success is about aligning efforts toward a common goal.
The Future of Life 19 implied HN points 22 Mar 24
  1. Superintelligent AI might naturally align with moral goodness. This is because as AI becomes smarter, it might understand and adopt moral values without needing direct human guidance.
  2. AI development could progress slower than we think. If it takes longer for AI to reach a superintelligent level, we could have more time to solve safety issues.
  3. Humans have worked together in the past to deal with big threats. There's a chance we could unite globally to address AI safety concerns if problems arise.
AI safety takes 39 implied HN points 15 Jul 23
  1. Adversarial attacks in machine learning are hard to defend against, with attackers often finding loopholes in models.
  2. Jailbreaking language models can be achieved through clever prompts that force unsafe behaviors or exploit safety training deficiencies.
  3. Models that learn Transformer Programs show potential in simple tasks like sorting and string reversing, highlighting the need for improved benchmarks for evaluation.
Engineering Ideas 19 implied HN points 25 Jan 24
  1. The Gaia Network aims to improve science by making research more efficient and accountable.
  2. The Gaia Network can assist in funding science by providing quantitative impact metrics for awarding prizes and helping funders make informed decisions.
  3. Gaia Network serves as a distributed oracle for decision-making, aiding in a wide range of practical applications from farming operations to strategic planning and AI safety.
Artificial General Ideas 1 implied HN point 08 Nov 24
  1. Amelia Bedelia highlights the problem of commonsense in AI. Just like her literal understanding leads to funny mishaps, AI can also misunderstand instructions without proper commonsense.
  2. It's important to consider that powerful AI shouldn't be seen as automatically dangerous. As AI gets more capable, it can also be more controllable if designed well.
  3. Many fears about AI assume it will behave like humans, but AI has different motivations and can take its time making decisions, so we shouldn't assume it will spontaneously want to harm us.
The Gradient 20 implied HN points 27 Feb 24
  1. Gemini AI tool faced backlash for overcompensating for bias by depicting historical figures inaccurately and refusing to generate images of White individuals, highlighting the challenges of addressing bias in AI models.
  2. Google's recent stumble with its Gemini AI tool sparked controversy over racial representation, emphasizing the importance of transparency and data curation to avoid perpetuating biases in AI systems.
  3. OpenAI's Sora video generation model raised concerns about ethical implications, lack of training data transparency, and potential impact on various industries like filmmaking, indicating the need for regulation and responsible deployment of AI technologies.
Engineering Ideas 19 implied HN points 27 Dec 23
  1. AGI will be made of heterogeneous components, combining different types of DNN blocks, classical algorithms, and key LLM tools.
  2. The AGI architecture may not be perfect but will be close to optimal in terms of compute efficiency.
  3. The Transformer block will likely remain crucial in AGI architectures due to its optimization, R&D investments, and cognitive capacity.
Vishnu R Nair 1 HN point 23 Jul 24
  1. AI companies often focus on getting their products out quickly, which can lead to unsafe practices. They might ignore safety just to beat the competition.
  2. Governments are struggling to create effective regulations for AI. If regulations are too strict, companies might move to places with fewer rules, which doesn't help safety.
  3. It's hard to agree on what 'safe AI' means because different people see it in different ways. Without clear definitions, holding anyone accountable for AI risks becomes complicated.
Lukasz’s Substack 3 HN points 17 Apr 24
  1. ControlAI's platform offers a solution for AI safety and compliance, simplifying the complex process for users.
  2. Users can use the platform to create an inventory of AI assets, understand regulations like ISO Norms and GDPR, and track progress towards compliance.
  3. The platform also enables users to deploy defenses, showcase AI safety solutions, and collaborate with the AI community to enhance safety measures.
Enshrine Computing 2 HN points 03 May 23
  1. Web4 is envisioned as the web where humans and AI work together, with data being autonomously generated and consumed.
  2. The transition from Web2 to Web4 emphasizes trust as a valuable resource for facilitating convenient interactions between autonomous agents.
  3. Enshrine Computing aims to advance autonomous computing by focusing on AI safety through trusted execution environments and computational secrecy.
The Future of Life 0 implied HN points 30 Mar 23
  1. AI has the potential to be very dangerous, and even a small chance of catastrophe is worth taking seriously. Experts have different opinions on how likely this threat is.
  2. Pausing AI research isn't a good idea because it could let bad actors gain an advantage. Instead, it's better for responsible researchers to lead the development.
  3. We should focus on investing in AI safety and creating ethical guidelines to minimize risks. Teaching AI models to follow humanistic values is essential for their positive impact.
Engineering Ideas 0 implied HN points 24 Apr 23
  1. Multiple theories of cognition and value should be used simultaneously for alignment.
  2. Focus on engineering the alignment process rather than trying to solve the alignment problem with a single theory.
  3. Having diversity in approaches across AGI labs can be more beneficial than sticking to a single alignment theory.