⏪ Reverse Engineering Prompts
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- 📰 News and Trends.
- Reverse Engineering Prompts.
- Diffuse: Create Unlimited AI Videos.
- No More NonCompete Contracts.
- Publications I am currently reading and recommending.
- Microsoft’s Phi-3 Small Language Models Lead the Way.
- 🧰 AI Tools (Gaming & 3D)
📰 AI News and Trends
- Apple is developing an AI server processor using TSMC’s technology, aiming for mass production by 2025 to enhance its data centers and AI tools. (MacRumors)
- AI Beauty pageants are coming. AI models take every toxic gendered beauty norm and bundle them up into a completely unrealistic package. (TheGuardian)
- OpenAI, Meta, and Google Sign On to New Child Exploitation Safety Measures. (WSJ)
- Ray-Ban’s Meta Smart Glasses integrate multimodal AI for object identification and quick answers, enhancing functionality while maintaining ease of use. (TheVerge)
- Startup uses AI to edit human DNA (Neoscope)
- Perplexity introduces Perplexity Enterprise Pro ($40 Monthly), raising $62.7 million for expansion. It accelerates research for companies like Databricks and Zoom, maintaining answer integrity amid potential ad sales. (TC)
🌐 Other Tech news
- Tesla teases its upcoming Uber-like self-driving ride-hailing app. (Electrek)
- TSMC’s Phoenix expansion is delayed to 2025 due to cultural clashes and integration challenges, raising concerns about its success despite significant investments. (RofTW)
- The Senate has passed a bill requiring TikTok’s parent company, ByteDance, to divest from the platform or face a U.S. ban, citing national security concerns. President Biden is expected to sign the bill, which gives ByteDance up to a year to sell TikTok. This legislation aims to protect U.S. user data from potential Chinese government influence and manipulation. (TheVerge)
- Apple reportedly cuts Vision Pro production due to low demand. (TheVerge)
Reverse Engineering Prompts
Reverse prompting is a technique used in interacting with AI models, particularly those involved in text generation, but can also be done with images, bu uploading an image and asking for a prompt to create such an image. It involves starting with the desired output or answer and working backward to create a prompt that will lead the AI to produce that specific outcome. This method can be particularly useful when you want the AI to generate content that aligns closely with specific goals or formats.
Reverse Engineering Prompts.
Step 1: Identify Desired Output
- Objective: Understand what makes the output successful.
- Example: Analyze a compelling article for key elements like topic depth and engaging arguments.
Step 2: Extract Core Elements
- Action: List essential components that define the output.
- Example: Identify themes such as “economic effects of climate change.”
Step 3: Construct the Prompt
- Task: Create a prompt incorporating these key elements.
- Example: “Write an in-depth analysis of the economic effects of climate change, including case studies and predictions.”
Step 4: Test and Refine
- Process: Use the prompt, evaluate the AI’s response, and refine as needed. Once the prompt yields consistent, desired outputs, you may be able to use it regularly.
- Example: Apply the refined prompt for creating similar content.
This technique is akin to an image search where you seek specific elements within an image that text searches fail to identify. By creatively using images, you can craft prompts to design similar products or concepts. Similarly, in text applications, this approach enables you to uncover more detailed and in-depth information about a particular topic.
Explore optimized prompts for a breadth of business and personal tasks.
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No More NonCompete Contracts.
The US Federal Trade Commission (FTC) has issued a final rule that bans most noncompete agreements, aiming to increase job mobility and wage growth.
This change is expected to generate 8,500 new businesses annually and increase average worker wages by $524 per year. Particularly impactful in the tech sector, where 36% of engineers and 35% of tech workers are currently restricted by noncompetes, the rule could boost innovation and entrepreneurship. While it may face legal challenges, such as those anticipated by the US Chamber of Commerce, it aligns with trends in states like California, where the absence of noncompetes has supported tech industry growth.
Microsoft’s Phi-3 Small Language Models Lead the Way
Microsoft Phi-3 vs. Other Models.\
The Phi-3 small language models (SLMs) from Microsoft offer cost-effective and flexible AI solutions, requiring less computational power and functioning offline. They excel in tailored tasks and are scalable to various devices.
However, they may not handle complex tasks as well as larger language models (LLMs) and might lack the same depth of knowledge and generalization. Despite this, Phi-3 models represent a strategic addition to AI tools, providing specific advantages where speed and flexibility are crucial. Microsoft’s Phi-3 series promises significant advancements in AI accessibility and performance, inspired by children’s learning and trained on high-quality datasets. These models, like Phi-3-mini with 3.8 billion parameters, are ideal for environments with limited connectivity or strict data privacy requirements. Available in the Microsoft Azure AI Model Catalog and on Hugging Face, a platform for machine learning models, as well as Ollama, a lightweight framework for running models on a local machine.
📰 Publications I am currently reading and recommending:
- Growth Forum — Learn how to build a repeatable sales process creating a pipeline full of qualified deals.
- 1-Minute Question — Based on Neuroscience Science Practices to rewire your brain for success.
- Secrets of Success — Mental Models for Success.
- How Brands Win — Distills the strategies behind great brands. And gives you actionable insights for your business.
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