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

Hard-forked! Casey Newton’s distorted portrait of Gary Marcus and AI skepticism

6679 implied HN points • 06 Dec 24
🕹 Technology AI Machine Learning Data Ethics Tech Policy Regulation
  1. We need to prepare for AI to become more dangerous than it is now. Even if some experts think its progress might slow, it's important to have safety measures in place just in case.
  2. AI doesn't always perform as promised and can be unreliable or harmful. It's already causing issues like misinformation and bias, which means we should be cautious about its use.
  3. AI skepticism is a valid and important perspective. It's fair for people to question the role of AI in society and to discuss how it can be better managed.

Satya Nadella and the three stages of scientific truth

8023 implied HN points • 23 Nov 24
🕹 Technology AI Innovation Science Computing Philosophy
  1. New ideas in science often face resistance at first. People may ridicule them before they accept the change.
  2. Scaling laws in deep learning may not last forever. This suggests that other methods may be needed to advance technology.
  3. Many tech leaders are now discussing the limits of scaling laws, showing a shift in thinking towards exploring new approaches.

ChatGPT, at Age Two

7074 implied HN points • 28 Nov 24
🕹 Technology AI Software Innovation Data Digital ethics
  1. ChatGPT has been popular for two years, but many of the initial uses people expected, like taking over Google, haven't happened. Companies are not as impressed with its real-world results.
  2. Despite promises of improvement, ChatGPT still struggles with inaccuracies and generating false information. Users continue to experience 'hallucinations' where the AI makes things up.
  3. The investment in AI is huge, but the fundamental issues with reliability and factual accuracy haven't improved significantly. There's a call for new approaches to make AI more trustworthy.

Which CEO will be the last to see it?

4624 implied HN points • 05 Dec 24
🕹 Technology AI Innovation CEOs Trends Industry
  1. Many people were skeptical about the hype around Generative AI during 2022 and 2023. Some experts believe that the truth about its capabilities will eventually become clear.
  2. Several tech leaders are starting to see and admit the limitations of current AI models. This signals a possible shift in how the industry views AI's effectiveness going forward.
  3. To achieve greater advancements, experts suggest integrating different methodologies, like neurosymbolic AI, which could help overcome current challenges in AI development.

An AI rumor you won’t want to miss

7153 implied HN points • 10 Nov 24
🕹 Technology AI Deep Learning Scaling Data Computing
  1. The belief that more scaling in AI will always lead to better results might be fading. It's thought we might have reached a limit where simply adding more data and computing power is no longer effective.
  2. There are concerns that scaling laws, which have worked before, are just temporary trends, not true laws of nature. They don’t actually solve issues like AI making mistakes or hallucinations.
  3. If rumors are true about a major change in the AI landscape, it could lead to a significant loss of trust in these scaling approaches, similar to a bank run.
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Two visions of AI’s future

4387 implied HN points • 05 Dec 24
🕹 Technology AI Future Ethics Regulation Society
  1. AI has two possible futures: one where it causes problems for society and another where it helps improve lives. It's important for us to think about which future we want.
  2. If AI is not controlled or regulated, it might lead to a situation where only the rich benefit, creating more social issues.
  3. We have the chance to develop better AI that is safe and fair, but we need to actively work towards that goal to avoid harmful outcomes.

Don’t Ride This Bike! Generative AI’s persistent trouble with compositionality and parts

3952 implied HN points • 08 Dec 24
🕹 Technology AI Machine Learning Image Processing Natural Language Generative models
  1. Generative AI struggles with understanding complex relationships between objects in images. It sometimes produces physically impossible results or gets details wrong when asked to create images from text.
  2. Recent improvements in AI models, like DALL-E3, show only slight progress in handling specifications related to parts of objects. It can still mislabel parts or fail to follow more complex requests.
  3. AI systems need to improve their ability to check and confirm that generated images match the prompts given by users. This may require new technologies for better understanding between language and visuals.

Casey (Newton) Strikes Out

3517 implied HN points • 11 Dec 24
🕹 Technology Artificial Intelligence Skepticism Ethics Industry Trends Innovation
  1. AI skeptics believe that while there were big improvements in AI, those gains seem to be slowing down now. They think the hype isn't matching reality.
  2. Casey Newton's view oversimplifies AI skepticism by dividing it into two groups, but many skeptics have different opinions and concerns about AI's influence.
  3. It's important to recognize the problems with AI and financial issues in the industry, rather than just celebrating advancements without addressing weaknesses.

Sora still appears to have trouble with physics

3636 implied HN points • 10 Dec 24
🕹 Technology AI Computer Science Data Physics Innovation
  1. Sora struggles to understand basic physics. It doesn't know how objects should behave in space or time.
  2. Past warnings about Sora's physics issues still hold true. Even with more data, it seems these problems won't go away.
  3. Investing a lot of money into Sora hasn't fixed its understanding of physics. The approach we're using to teach it seems to be failing.

8 signs that Donald Trump has a progressive form of dementia

7390 implied HN points • 02 Nov 24
🇺🇸 U.S. Politics Media Criticism Public Opinion Election Commentary
  1. There are signs that suggest Donald Trump may have a form of dementia, including issues with memory and inappropriate behaviors.
  2. The media is not fully addressing Trump's mental health concerns, even as they report individual incidents that raise alarm.
  3. Experts and caregivers should speak out about Trump's condition to ensure the public understands the potential risks for the future of the presidency.

The new AI scaling law shell game

4663 implied HN points • 24 Nov 24
🕹 Technology Artificial Intelligence Machine Learning Computing Data Analysis
  1. Scaling laws in AI aren't as reliable as people once thought. They're more like general ideas that can change, rather than hard rules.
  2. The new approach to scaling, which focuses on how long you train a model, can be costly and doesn't always work better for all problems.
  3. Instead of just trying to make existing models bigger or longer-lasting, the field needs fresh ideas and innovations to improve AI.

PSA: Microsoft may be training on your private data without your knowledge

4070 implied HN points • 26 Nov 24
🕹 Technology AI Data Privacy Big Tech Ethics Consumer Rights
  1. Microsoft might be using your private documents to train their AI without you knowing. It's important to check your settings.
  2. If you have sensitive information in your Office documents, make sure to turn off any options that share your data.
  3. Big tech companies are increasingly using sneaky methods to gather training data, so it's vital to stay informed and protect your privacy.

On hype, and the unbearable banality of ChatGPT’s poetry

4466 implied HN points • 19 Nov 24
🕹 Technology AI Poetry Literature Critique Research
  1. A recent study claims that ChatGPT's poetry is similar to Shakespeare's, but it's important to be skeptical of such bold claims. Many experts believe the poetry is just a poor imitation, lacking genuine creativity.
  2. The critique of the AI poetry highlights that it often reads like the work of an unskilled poet who doesn't truly understand the style they're trying to emulate. This raises questions about the quality of AI-generated content.
  3. It's essential to approach AI-generated work with caution and to not get swayed by hype, as popular claims may not always reflect the true abilities of the technology.

AI influencer hype gone wild

5572 implied HN points • 31 Oct 24
🕹 Technology Artificial Intelligence Productivity Tools Tech Trends Market Analysis Consumer behavior
  1. Many people are trying AI tools, but not everyone thinks they are effective. This shows there's a mix of interest and skepticism in using new technology.
  2. A recent survey revealed that while 79% of people have tried Microsoft Copilot, only 25% found it worthwhile. This indicates people are testing AI but still unsure about its overall value.
  3. People are not ignoring AI; they are being cautious and waiting to see if it meets their expectations before fully committing. It’s a wait-and-see attitude towards technology.

Cognitive scientist Gary Marcus says AI must be regulated. He has a plan.

3003 implied HN points • 27 Nov 24
🕹 Technology AI Ethics Regulation Cognitive Science Policy AGI
  1. AI needs rules and regulations to keep it safe. It is important to have a plan to guide this process.
  2. There is an ongoing debate about how different regions, like the EU and US, approach AI policy. These discussions are crucial for the future of AI.
  3. Experts like Gary Marcus share insights about the challenges and possibilities of AI technology. Listening to their views helps understand AI better.

An epidemic of weirdly precise AI butt facts

4703 implied HN points • 30 Oct 24
🕹 Technology AI Investments Future Trends Innovation Predictions
  1. Elon Musk and others often make bold claims about AI's future, but many of these predictions lack proper evidence and are overly optimistic.
  2. Investors are drawn to grand stories about AI that promise big returns, even when the details are vague and uncertain.
  3. The exact benefits of advanced AI, like machines being thousands of times smarter, are unclear, and it's important to question how that would actually be useful.

Update re: Microsoft and training data

2766 implied HN points • 26 Nov 24
🕹 Technology Artificial Intelligence Data Privacy Machine Learning Software Development Corporate Communication
  1. Microsoft claims they don't use customer data from their applications to train AI, but it's not very clear how that works.
  2. There is confusion around the Connected Services feature, which says it analyzes data but doesn't explain how that affects AI training.
  3. People want more clear answers from Microsoft about data usage, but there hasn't been a detailed response from the company yet.

Death of a Chatbot, body blow to an industry

4703 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, Sora has not “learned physics”

3596 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.

Sora Can’t Handle the Truth

3398 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.

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

3122 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.

The Year of the Big-Balled Rat

2687 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

Absolutely amazing ant video augurs intellectual mayhem

3043 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.

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

4782 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.

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

2608 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.

Serious medical error from Perplexity’s chatbot

2489 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.

Further Trouble in Hinton City

2687 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

Elon Musk sues OpenAI

2292 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

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

2489 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.