🤖Apple Dominates Wall Street's AI Market, Samsung Not Far Behind.
Plus: Mistral AI and OpenAI Launch New Mini Models Separately.
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The weekend has arrived—a perfect time for both enjoyment and introspection in our ever-busy world. In this edition, we explore how AI can foster deep, introspective thinking. We also cover the recent releases of more affordable models by Mistral AI and OpenAI and delve into how Apple is successfully selling AI to Wall Street. Enjoy this issue and have a wonderful weekend!
📰 News and Trends.
Mistral AI and OpenAI Launch New Mini Models Separately.
Apple Dominates Wall Street's AI Market, Samsung Not Far Behind.
🧰 AI Tools (Design II)
Harnessing AI for Deep Introspection and Challenging Questions.
📰 AI News and Trends
US Floats Tougher Trade Rules to Rein In China Chip Industry (Bloomberg)
Tech companies are developing a new generation of AI assistants that can not only write code but debug, organize, and critique it, too (Wired)
AI App that claimed to detect STDs from Dick Picks Shuts down after failing to work, but with today’s computer vision capabilities, the next one may (TheByte)
YouTubers Furious After Apple and Anthropic Steal Their Data to Train AI (Yahoo)
The ‘godmother of AI’ has a new startup already worth $1 billion (TheVerge)
🌐 Other Tech news
And just like that, all our tech can be gone. Huge Microsoft Outage Linked to CrowdStrike Takes Down Computers Around the World (Wired)
EssilorLuxottica, which owns Ray-Ban, is buying Supreme for $1.5 billion in its first move outside the eyewear space and Meta did not waste any time and is talking with EssilorLuxottica to buy a 5% stake in the company.
Why Silicon Valley’s Democrats Lost Their Voice on Trump (TheInformation)…
… Is Silicon Valley’s support of Trump a Bitcoin play? Mar Cuban thinks so (ThreadReader)
New Camera Inside Cars Detects if you’ve been drinking (TheByte)
Mistral AI and OpenAI Launch New Mini Models Separately.
All technology becomes more accessible and affordable with time. Mobile phones used to be brick-sized, costly, and conspicuous items only affordable to a few and now they are ubiquitous worldwide and soon to become disposable items. Ai seems to follow that path. OpenAI has launched a new, cost-effective model called GPT-4o Mini, targeting developers seeking affordable AI tools. This model, cheaper and more capable than its predecessor GPT-3.5, supports diverse functions including text and vision. It’s designed to be accessible on various OpenAI plans, with availability expanding to enterprise users soon. GPT-4o Mini outperforms GPT-3.5 on benchmark tests like MMLU and has been adopted by companies like Ramp and Superhuman to streamline tasks such as data extraction from receipts and email auto-suggestions. This release reflects OpenAI’s strategic shift towards providing smaller, economically viable models for broader use in tech development.
Mistral AI, the French LLM company has also launched a Mini model. Mistral NeMo has been released in partnership with NVIDIA. A 12B model featuring a 128k token context and excelling in multilingual performance. It integrates easily with existing systems, supports extensive language capabilities, and employs a new, efficient tokenizer, Tekken. Mistral NeMo is available for trial and adaptation via platforms like HuggingFace and is positioned as a robust tool for developers and researchers globally.
Apple Dominates Wall Street's AI Market, Samsung Not Far Behind.
Apple has effectively engaged Wall Street with its strategic entry into the AI market, despite joining the AI race later than its competitors. Apple's methodical approach has paid off, especially evident when its stock reached an all-time high following Morgan Stanley's endorsement. This optimism is fueled by predictions of a substantial upgrade cycle, propelled by the anticipated launch of Apple's AI tools, which will initially be available to a limited 8% of existing iPhone and iPad users.
Apple's success contrasts with the struggles faced by others in the industry, who have experienced public setbacks and internal issues. By focusing on practical, everyday applications of AI, Apple has positioned its products as both innovative and indispensable within its ecosystem. This strategy not only revitalizes interest in its hardware but also cleverly extends Apple's renowned "walled garden" approach into the realm of AI, differentiating it from competitors like Google and Microsoft.
In comparison, Samsung has adopted a more aggressive rollout of its AI services, aiming to quickly expand its user base and encourage app development for its Galaxy AI platform. Both tech giants continue to vie for consumer interest in generative AI applications, a market still in its infancy and not expected to significantly impact purchasing behaviors until at least 2025.
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Design II
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Harnessing AI for Deep Introspection and Challenging Questions.
In today's fast-paced world, it's easy to get lost in our routines and established ways of thinking. Amidst this, recognizing the multitude of perspectives that shape our society and the potential manipulation of our education and information systems becomes a formidable challenge. This makes introspection crucial. We need to continually question our own biases and the validity of our thoughts. Engaging in introspection not only enhances our performance in relationships, work, and social circles, but it also deepens our self-awareness and broadens our understanding of the world. While technology, including AI tools, can be a valuable aid in this process, it is not a substitute for the nuanced understanding that comes from conversations with human professionals.
Today we share some tools on how to use AI effectively for introspection and self-reflection, you can approach it by explicitly requesting that it generates questions tailored to explore various aspects of your life, feelings, or decisions. Here’s how you might structure your request:
Define the Area of Focus: Clearly state the topic or area of your life you wish to reflect upon. This could be career, relationships, personal growth, health, or any other specific aspect.
Request Open-Ended Questions: Ask ChatGPT (or your favorite LLM) to provide open-ended questions that encourage deep thinking and reflection. Open-ended questions typically begin with "what," "how," "why," or "tell me about."
Specify Depth or Complexity: If you prefer questions that challenge you more deeply, mention that you want questions that help you explore underlying reasons or long-term impacts.
Example Prompts:
Career Reflection: Can you help me reflect on my career path? Please ask me some deep, open-ended questions about my job satisfaction and future aspirations.
Personal Relationships: I want to understand my relationships better. Could you ask me some questions that will help me think about my role and interactions in my personal relationships?
Self-Improvement: Please provide me with some introspective questions about my recent actions towards self-improvement. I'm interested in understanding my motivations and how I can improve.
Life Choices: I'm at a crossroads and need to think about my next steps. Can you generate some reflective questions that help me consider the impact of my potential decisions?
Tips for Using ChatGPT for Introspection
Iterative Process: Use ChatGPT's responses as a starting point and feel free to refine or ask for different questions based on your initial reflections.
Record Your Thoughts: Writing down your answers to these questions can enhance your reflection process, making it easier to track your thoughts and progress over time.
Follow-Up Questions: After answering a question, you can ask ChatGPT to help you dive deeper into your response by asking for follow-up questions based on your answer.
By structuring your requests with these points, AI can become a valuable tool in your introspective practices, helping you gain insights into your thoughts and behaviors.
During the past two days of using the GPT-4o Mini experience, the response speed is indeed fast. However, if the task volume is large, such as over 1000 words of output, GPT-4o Mini will have the common problems of all small models, which are inaccurate output and truncated information.