The hottest Generative AI Substack posts right now

ChatGPT, Gemini, and Claude are three major AI models competing for a significant opportunity, striving to work with companies like Apple for future advancements.
Apple is seeking AI partnerships globally to enhance iPhones with AI capabilities, underlining a serious commitment to integrating generative AI technology.
The collaboration between Apple and OpenAI to integrate generative AI into iPhones in 2024 demonstrates a major step towards enhancing user experience and functionality.

AI gadgets play an important role in helping people understand Artificial Intelligence.
Technologies often go through phases of awareness, evaluation, and adaptation in society.
Playing with AI gadgets is crucial for learning and innovation, regardless of their success.

AI may not live up to the grand promises or catastrophic fears set for it, but change is inevitable as with past technologies.
There's a real possibility that AI might just fizzle out due to factors like limited electricity, quantum computing breakthroughs, or water scarcity.
Generative AI tools could reach a limit in their advancements, settling to quietly assist in mundane or important tasks rather than revolutionize entire industries.

Search engines face challenges similar to newspapers did with increasing ads and advertorial content, blurring lines between sponsored and genuine content.
Consumers are now more aware of SEO tactics and the dominance of ads on search engines, leading them to seek valuable results on second or third pages.
There's a shift in how people want and expect to search, leaning towards in-app search features and a desire for context-driven results over mere links.

Cryptocurrencies and blockchain technologies may face challenges from criminal activity and mass disillusionment, similar to what AI may encounter.
Fake websites generated by AI, AI-written spam emails, and AI scams highlight potential risks associated with the widespread use of artificial intelligence.
Criminals, hackers, and scammers exploiting AI could inadvertently lead to a societal distrust of AI and a shift towards more human-centric approaches, potentially preventing the negative impacts of artificial intelligence on humanity.

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Large Language Models (LLMs) can learn better when given contextual information, which helps them be more accurate and reduce mistakes.
Retrieval-augmented generation (RAG) is a useful method because it allows models to customize responses without needing a lot of extra training.
Even with good context, LLMs can still create some incorrect responses, showing that they sometimes mix up information in a believable way.

OpenAI's JSON mode doesn't ensure a specific output format, but it guarantees that the JSON will be valid. This means it will always parse without errors.
Using the 'seed' parameter can help create consistent JSON structures, allowing similar inputs to produce the same output format.
It's important to explicitly instruct the model to generate JSON to avoid issues; relying solely on the response format flag might lead to problems like infinite outputs.

Prompt engineering is important for getting the best responses from large language models. Users have to carefully design prompts to mimic what they want the model to generate.
Static prompts can be turned into templates with placeholders that can be filled in later. This makes it easier to reuse and share prompts in different situations.
Prompt pipelines allow users to create more complex applications by linking several prompts together. This helps organize how information is processed and improves user interaction with chatbots.

Using Generative AI can save a lot of time when creating drafts for legal documents. Lawyers at Ashurst found they could save up to 80% of the time on some tasks.
The accuracy of AI-generated content can be surprisingly high compared to human output, but it still requires careful review. Lawyers found it hard to tell whether some AI outputs were made by a human or the AI.
When pitching to fund selectors, having a clear story and understanding your audience is key. Many pitch decks fail because they don't address who their target customers are or why now is the right time for their proposal.