Marcus on AI

Marcus on AI critically explores the advancements, limitations, ethical considerations, and societal implications of artificial intelligence technologies. Through detailed analysis, it discusses issues like AI's understanding of math, transparency in AI development, AI risks, copyright infringement by AI, and the potential misuse of AI in various sectors.

AI Advancements and Limitations Ethics and AI AI in Society AI and Law AI for Military Strategy Environmental Impact of AI AI in Healthcare AI and Education AI and Jobs AI Policy and Regulation

The hottest Substack posts of Marcus on AI

And their main takeaways

The Year of the Big-Balled Rat

2682 implied HN points • 14 Mar 24
🔬 Science GenAI AI Impact
  1. GenAI is causing issues in science, with errors in research papers being linked to AI
  2. Using AI for writing and illustration might have negative impacts on the quality and credibility of scientific research
  3. The use of LLMs in research articles could lead to a decline in reputation for journal publishers and potential consequences for the science community

No, Sora has not “learned physics”

3589 implied HN points • 02 Mar 24
🕹 Technology AI Physics Modeling
  1. Sora is not a reliable source for understanding how the world works, as it focuses more on how things look visually.
  2. Sora's videos often depict objects behaving in ways that defy physics or biology, indicating a lack of understanding of physical entities.
  3. The inconsistencies in Sora's videos highlight the difference between image sequence prediction and actual physics, emphasizing that Sora is more about predicting images than modeling real-world objects.

The Irony and the Agony of Elon Musk's Lawsuit against OpenAI

3116 implied HN points • 03 Mar 24
🕹 Technology AI Lawsuit Mission Ethics Innovation
  1. Elon Musk's lawsuit against OpenAI highlights how the organization changed from its initial mission, raising concerns about its commitment to helping humanity.
  2. The lawsuit emphasizes the importance of OpenAI honoring its original promises and mission, rather than seeking financial gains.
  3. The legal battle between Musk and OpenAI involves complex motives and the potential impact on AI development and its alignment with humane values.

Death of a Chatbot, body blow to an industry

4693 implied HN points • 17 Feb 24
🕹 Technology Chatbots Ethics AI
  1. A chatbot provided false information and the company had to face the consequences, highlighting the potential risks of relying on chatbots for customer service.
  2. The judge held the company accountable for the chatbot's actions, challenging the common practice of blaming chatbots as separate legal entities.
  3. This incident could impact the future use of large language models in chatbots if companies are held responsible for the misinformation they provide.

No, RAG is probably not going to rescue the current situation

3392 implied HN points • 23 Feb 24
🕹 Technology Artificial Intelligence Machine Learning Tech industry AI Ethics Research
  1. In Silicon Valley, accountability for promises is often lacking, especially with over $100 billion invested in areas like the driverless car industry with little to show for it.
  2. Retrieval Augmentation Generation (RAG) is a new hope for enhancing Large Language Models (LLMs), but it's still in its early stages and not a guaranteed solution yet.
  3. RAG may help reduce errors in LLMs, but achieving reliable artificial intelligence output is a complex challenge that won't be easily solved with quick fixes or current technology.
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Serious medical error from Perplexity’s chatbot

2485 implied HN points • 29 Feb 24
🏥 Health & Wellness Chatbot Advice
  1. A serious medical error occurred in Perplexity's chatbot when giving post-surgery advice, showing the dangers of generative pastische.
  2. The error was due to combining specific advice for sternotomy with generic advice on ergonomics, potentially causing harm to the patient's recovery.
  3. This incident highlights the importance of caution in relying on chatbots for medical advice, as they can still provide inaccurate or harmful recommendations.

Happy 1st Birthday, GPT-4

1380 implied HN points • 16 Mar 24
🕹 Technology AI Ethics Applications Progress Competition
  1. There seems to be a possible plateau in GPT-4's capability, with no one decisively beating it yet.
  2. Despite challenges, there has been progress in discovering applications and putting GPT-4 type models into practice.
  3. Companies are finding putting Large Language Models into real-world use challenging, with many initial expectations proving unrealistic.

Sora Can’t Handle the Truth

3392 implied HN points • 17 Feb 24
🕹 Technology AI Data Errors Training Data Images
  1. Large language models like Sora often make up information, leading to errors like hallucinations in their output.
  2. Systems like Sora, despite having immense computational power and being grounded in both text and images, still struggle with generating accurate and realistic content.
  3. Sora's errors stem from its inability to comprehend global context, leading to flawed outputs even when individual details are correct.

Elon Musk sues OpenAI

2287 implied HN points • 01 Mar 24
🇺🇸 U.S. Politics Legal Technology
  1. Elon Musk is suing OpenAI and key individuals over alleged breaches and shifts in mission
  2. The lawsuit highlights a lack of candor and a departure from the original nonprofit mission of OpenAI
  3. Elon Musk's focus is on ensuring OpenAI returns to being open and aligns with its original mission

Absolutely amazing ant video augurs intellectual mayhem

3037 implied HN points • 18 Feb 24
🕹 Technology Technology impact
  1. An astonishing video of ants raises concerns about the spread of misleading content through advanced technology.
  2. Fake videos with educational content could fool many people and harm important learning resources.
  3. The rise of photorealistic fake videos threatens to deceive viewers, affecting education and awareness.

Has Google gone too woke? Why even the biggest models still struggle with guardrails

2603 implied HN points • 21 Feb 24
🕹 Technology AI Ethics Data Bias Machine Learning
  1. Google's large models struggle with implementing proper guardrails, despite ongoing investments and cultural criticisms.
  2. Issues like presenting fictional characters as historical figures, lacking cultural and historical accuracy, persist with AI systems like Gemini.
  3. Current AI lacks the ability to understand and balance cultural sensitivity with historical accuracy, showing the need for more nuanced and intelligent systems in the future.

Further Trouble in Hinton City

2682 implied HN points • 08 Feb 24
🕹 Technology AI Data Research Experts Machine Learning
  1. Recent evidence challenges claims of Generative AI systems not storing things or understanding them deeply
  2. Trivial perturbations affect GenAI systems significantly, indicating a lack of deep understanding
  3. GenAI systems effectively store things but struggle with novel designs and understanding simple concepts

What Could Possibly Go Wrong with Sam Altman’s New Ambitions?

2485 implied HN points • 09 Feb 24
🕹 Technology AI Security Finance Ethics Risk
  1. Sam Altman's new ambitions involve projects with significant financial and technological implications, such as automating tasks by taking over user devices and seeking trillions of dollars to reshape the business of chips and AI.
  2. There are concerns about the potential consequences and risks of these ambitious projects, including security vulnerabilities, potential misuse of control over user devices, and the massive financial implications.
  3. The field of AI may not be mature enough to handle the challenges presented by these ambitious projects, and there are doubts about the feasibility, safety, and ethical implications of executing these plans.

“Math is hard” — if you are an LLM – and why that matters

4772 implied HN points • 19 Oct 23
🔬 Science Mathematics Artificial Intelligence Machine Learning
  1. Even with massive data training, AI models struggle to truly understand multiplication.
  2. LLMs perform better in arithmetic tasks than smaller models like GPT but still fall short compared to a simple pocket calculator.
  3. LLM-based systems generalize based on similarity and do not develop a complete, abstract, reliable understanding of multiplication.

Karen Bakker, 1971-2023

3510 implied HN points • 07 Sep 23
🎨 Art & Illustration Tribute Obituary Inspiration
  1. Karen Bakker was a visionary with broad interests and expertise
  2. She was a successful academic, global adventurer, and political leader
  3. Karen Bakker's work focused on using AI to improve animal communication and addressing environmental dilemmas

OpenAI’s Lies and Half-Truths

76 HN points • 15 Mar 24
🕹 Technology Artificial Intelligence Transparency Regulation Data Training
  1. OpenAI has been accused of not being completely candid in their communications and responses to questions.
  2. There have been instances where OpenAI's statements may not accurately reflect their true intentions or actions.
  3. Concerns have been raised about OpenAI's transparency regarding their data training sources, financial matters, regulation views, and future plans.

OpenAI’s “Own Goal”

98 HN points • 06 Mar 24
🕹 Technology AI Ethics Copyright Racism Innovation
  1. OpenAI's mission of being open-source and collaborative has shifted over the years, leading to concerns about transparency and integrity.
  2. Email communications between OpenAI and Elon Musk raised doubts about the organization's commitment to its stated mission of open-sourcing technology.
  3. Recent incidents of covert racism, copyright infringements, and violent content generated by OpenAI's technology have raised questions about the ethical impact of their work.

Seven reasons why the world should say No to Sam Altman

61 HN points • 10 Feb 24
🕹 Technology AI Energy Economics Human Capital
  1. Investing $7 trillion in AI infrastructure would have significant energy and climate implications, possibly leading to heavy environmental costs.
  2. $7 trillion for AI exceeds the economic resources allocated to critical areas like education or ending world hunger, highlighting potential opportunity costs.
  3. Such a massive financial risk of a $7 trillion project could have severe consequences on the world economy, similar to the impact of the 2007-2008 financial crisis.