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Unlock Faster AI Tools, Real-Time Collaboration, and the Future of AI Memory

From Black Forest Labs’ lightning-fast image generation to OpenAI’s new AI-powered editor, learn how the latest tools can boost your workflow and see what’s next for AI memory and smart homes.

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Personal Note:

After years away from the education space (aside from a few podcasts here and there), I’m excited to announce the launch of my new YouTube channel, Brent Builds AI!

For those of you who have been following my newsletter and Facebook posts, you already know I've been diving deep into automations and AI builds. The feedback has been incredible, and a lot of you have asked to see the processes in action. So, it’s finally time, I’ll be sharing all of my automations, AI builds, tips, tricks, new tools, and more on a weekly basis, for FREE.

I haven't done video content in years, but I’m back and ready to share everything I’m working on, straight to your screen. But here's the thing: I need to reach 1,000 subscribers before YouTube will let me share links to documents, tools, and more in my video descriptions. šŸš«šŸ“„

To sweeten the deal, I’m doing a giveaway for the first 1,000 subscribers:

1 lucky winner will get a 30-minute phone call where I’ll help you build an automation for your business or personal project.

1 more lucky winner will get a 30-minute call to ask me anything and pick my brain on whatever topic you want.

The first video drops this Friday, and I’ll be showing you how I automated generating 3,500+ pieces of content for under $10. šŸš€

So, if you’ve been digging what I’ve been sharing, please, please, please (with a cherry on top šŸ’) hit that Subscribe button! It only takes a second, and it would mean the world to me.

Black Forest Labs Just Dropped Flux 1.1 Pro: Here's Why You Should Care

Quick Byte:

Black Forest Labs (BFL)—the same team behind the wildly popular Stable Diffusion—just announced Flux 1.1 Pro, their new faster text-to-image AI model, and it’s available now via API. What does this mean? Essentially, developers and businesses can now integrate high-speed AI image generation into their apps, powering everything from ad creatives to visual designs. If you're into cutting-edge AI tools, this is big news.

Key Takeaways:

  • Faster and Better: Flux 1.1 Pro delivers 6x faster generation speeds than its predecessor, all while boosting image quality, prompt accuracy, and diversity.

  • API Access: BFL has launched an API that developers can use to build custom apps or improve existing ones with this powerful image generation tool. Pricing is competitive—4 cents per image.

  • Top of the Charts: Tested secretly under the code name ā€œBlueberry,ā€ Flux 1.1 Pro now holds the highest ELO score on the Artificial Analysis image arena leaderboard, surpassing models like Midjourney 6.1 and Ideogram v2.

  • Improved Speed for Flux 1.0 Pro: If you’re still using Flux 1.0 Pro, no worries. BFL has also doubled its speed, making it more efficient for existing users.

  • Scaling Up: With their recent $31 million funding round and backing from heavy hitters like Andreessen Horowitz, BFL isn’t slowing down. Expect more innovations, including potential text-to-video systems, which could shake up the entire media and content creation industry.

Bigger Picture:

Black Forest Labs is making a clear push to dominate the generative AI landscape, positioning Flux 1.1 Pro as a major player. Their proprietary models are fast, scalable, and increasingly used by enterprises for things like advertising and design. Plus, their API rollout means more developers can jump in and start building with these tools. It’s no longer just about image generation for a small set of users—this technology is becoming a go-to for businesses looking to streamline creative production at scale. As generative AI continues to evolve, BFL is expanding beyond images, hinting at future developments in video and even VR.

OpenAI Just Dropped Canvas—An AI-Powered Writing and Code Editor That's a Game-Changer

Quick Byte:

OpenAI just launched ChatGPT Canvas—an AI-first text and code editor. If you thought ChatGPT was powerful before, this takes it to a whole new level by letting you directly collaborate with AI to edit writing or code, in real-time. It’s designed to give you way more control and precision over your projects. Instead of scrolling up and down in a chat, you now have a side-by-side editor where AI is no longer just an assistant—it’s a real-time collaborator.

Key Takeaways:

  • What is Canvas? It's an advanced editor that allows you to directly interact with AI for writing and coding. Think of it as a fusion of ChatGPT, Google Docs, and a code editor, but with OpenAI's unique twist.

  • Why It’s Different: You can now edit any piece of text or code in real-time. No more losing your flow while scrolling through a long chat thread to make revisions. Canvas is like having an AI-powered project partner who makes suggestions, gives feedback, and adapts your work alongside you.

  • How It Works: Once enabled, Canvas opens up a separate window where you can work on writing or code projects. You can highlight sections for the AI to focus on, much like a copy editor or code reviewer.

  • Collaborator, Not Just a Tool: Canvas isn't about replacing your work—it’s about collaborating with AI. Whether you want feedback on a single sentence or need to adapt an entire project, Canvas offers precision and control without breaking your creative flow.

  • Exclusive Access: It's currently available in beta for Plus and Team subscribers, with Enterprise and Education users gaining access next week.

Bigger Picture:

This launch marks a significant shift in how we work with AI. ChatGPT Canvas moves beyond basic Q&A or task completion and into the realm of real-time, dynamic collaboration. You’re no longer simply asking for AI’s help and tweaking things after the fact—now you’re building, editing, and refining projects together, side-by-side. For developers and writers, this could be a game-changer, offering unprecedented speed and accuracy in real-time collaboration.

OpenAI has big plans to rapidly expand Canvas, likely adding features like DALL-E integration, richer editing tools, and potentially managing multiple canvases within a single session. For now, it’s clear that Canvas is shifting the paradigm of how we interact with AI, making it less of a tool and more of a co-creator.

Microsoft AI CEO: Long-Term Memory is the Next Big Thing in AI

Quick Byte:

Mustafa Suleyman, the CEO of Microsoft AI, believes long-term memory is the key to unlocking future AI experiences. At Madrona’s IA Summit, he discussed how AI's future hinges on its ability to remember and build deeper relationships with users. It’s not just about IQ and EQ—it's about memory, which could transform how we interact with AI in the next 18 months.

Key Takeaways:

  • Long-Term Memory is the Game-Changer: Microsoft’s Copilot is impressive, but it currently doesn’t retain info between sessions. According to Suleyman, figuring out how to add long-term memory will be the key to making AI even more personal and useful. He predicts AI systems with strong memory will emerge within 18 months.

  • AI Isn’t Just a Tool, It’s a Relationship: Suleyman says we're moving beyond thinking of AI as just an application. ā€œWe’re engineering personality,ā€ he said. AI systems are evolving into something like long-term companions—understanding us, adapting, and responding like a human.

  • AI’s Core Strengths: IQ, EQ, AQ: AI is getting smarter (IQ), more emotionally intelligent (EQ), and more capable of taking actions for users (AQ). The missing piece, though, is a system that can remember past interactions and use that info to make smarter decisions over time.

  • Forget AGI for Now: Suleyman downplays the obsession with artificial general intelligence (AGI) and instead suggests we focus on AIs that can zero in on the right info at the right time. In his view, combining IQ, EQ, AQ, and memory would create incredibly powerful systems that go beyond today’s context-limited AIs.

Bigger Picture:

Suleyman’s vision is clear: AI’s future isn’t just about one-off interactions. It’s about building ongoing relationships where the system remembers what you talked about last week, what tasks you prefer, and even how you like your emails drafted. Memory will allow AI to shift from being a reactive assistant to a proactive partner, anticipating needs and making informed decisions across time.

AI Will Be Running Your Home in Just a Few Years, Says SoftBank’s Masayoshi Son

Quick Byte:

Masayoshi Son, the founder of SoftBank, just predicted that artificial intelligence will take over everyday household tasks in as little as two to three years. From buying groceries to tutoring kids and even running your bath, Son believes AI personal agents are on the verge of transforming how we live—bringing a future where AI’s top mission will be to ensure our happiness.

Key Takeaways:

  • AI Household Management: Son predicts AI could run households within the next 2–3 years, handling everything from grocery shopping to health monitoring.

  • Human-Like Reasoning: Citing OpenAI’s latest model, Son says AI is already mimicking human reasoning, and will soon expand into highly complex tasks, like increasing savings or optimizing electric car performance.

  • AI’s Mission for Happiness: Future AI, Son claims, will aim to maximize our happiness by understanding our emotions and managing our daily lives to cater to them.

  • Big Investment in AI Chips: SoftBank is backing AI development in a big way, participating in a $6.6 billion funding round for OpenAI and potentially investing $100 billion in AI chip technology to support these advancements.

Bigger Picture:

AI taking over household tasks sounds revolutionary, but it's also a leap into uncharted territory. While Son paints a utopian vision of AI ensuring our happiness, we must also consider the implications of giving that much control to machines. What happens if the AI’s version of "happiness" doesn't align with our own? And as SoftBank pours billions into AI chip development, the race to bring these innovations to life will have huge stakes for both tech companies and consumers. The potential for AI in our homes is massive, but with that comes the need for caution and thoughtful regulation.

10 Ways to Use Notebook LM

Authors:

Yuling Shi (Shanghai Jiao Tong University), Songsong Wang (UC Davis), Chengcheng Wan (East China Normal University), and Xiaodong Gu (Shanghai Jiao Tong University)

Why This Paper is a Big Deal:

This research tackles one of the biggest issues in AI-powered code generation: making it bug-free. You might get a shiny new block of code from your AI assistant (think GPT-4), but chances are, it's going to need some human TLC to work correctly. Enter MGDebugger, a fresh new approach that takes AI debugging to the next level. Instead of fixing the code all at once (like slapping a band-aid on a leaky boat), this system breaks it down into manageable chunks, debugging each piece independently. The result? 18.9% better accuracy than previous methods, with a whopping 97.6% success rate in fixing code errors. Boom!

Summary:

The researchers developed a novel debugging system called MGDebugger, which uses a hierarchical approach to systematically fix errors in code generated by large language models (LLMs) like GPT-4. Unlike traditional debugging, which treats the code as a whole, MGDebugger splits the code into smaller subfunctions and fixes them piece by piece. The AI checks each part for bugs—starting from the smallest—and moves up, ensuring no error goes unnoticed. It also simulates code execution using an AI-powered "Python executor" to pinpoint where things go wrong.

What Makes It Important:

AI-generated code is already powerful but still error-prone, especially when tackling complex problems. MGDebugger solves this by introducing a smarter, hierarchical debugging process that doesn't just fix the code—it systematically hunts down bugs, from low-level syntax issues to high-level algorithmic flaws. This could make AI-generated code more reliable and practical, allowing companies to trust it for critical tasks without constant human oversight.

Use Cases Today:

  • Software Development: AI-powered tools using MGDebugger could help software developers clean up code faster and with fewer errors, making the development process more efficient.

  • Automated Testing: MGDebugger could integrate with continuous integration/continuous deployment (CI/CD) pipelines to automatically debug code as it is developed, saving time for engineers.

  • AI Education Tools: This approach could help teach coding more effectively by showing step-by-step debugging, enhancing learning experiences in programming education.

Future Impact:

MGDebugger has the potential to revolutionize how we handle code generation and debugging. As AI models become more prevalent in software development, this hierarchical approach could significantly reduce human oversight and speed up the debugging process. It’s not just about making code error-free—it’s about making AI code generation more reliable across industries, from fintech to healthcare. In the future, debugging could be fully automated, allowing developers to focus on innovation rather than fixing bugs.

In short, MGDebugger is about to make debugging code generated by AI a lot less of a headache—and that’s great news for anyone who relies on AI tools to create code.

Use AI as Your Personal Assistant

Ready to embrace a new era of task delegation?

HubSpot’s highly anticipated AI Task Delegation Playbook is your key to supercharging your productivity and saving precious time.

Learn how to integrate AI technology into your processes, allowing you to optimize resource allocation and maximize output with precision and ease.

9 Day Email Blitz:

I need help creating a 9-day email sequence for my upcoming product launch. Here are the details:
[INSERT PRODUCT DESCRIPTION]
Please create a 9-day email sequence that builds anticipation, overcomes objections, and drives sales. The sequence should include:

Day 1: Announcement email (3 days before launch) - Build excitement and give a sneak peek of what's coming
Day 2: Pre-launch content (2 days before launch) - Provide valuable content related to the product's topic
Day 3: Personal story/transformation email (1 day before launch) - Share your journey and how it relates to the product
Day 4: Launch day email - Announce that doors are open and highlight key benefits
Day 5: Benefit-oriented email - Deep dive into the transformative power of your offer
Day 6: Case study or testimonial email - Share a success story to build credibility
Day 7: Overcome objections email - Address common concerns and hesitations
Day 8: Urgency email with FAQ - Remind subscribers that time is running out and address frequently asked questions
Day 9: Last chance email - Final call to action before doors close

For each email, please provide:

A compelling subject line that entices opens
A brief outline of the email content
Key points to cover
A strong call-to-action

The emails should be written in a conversational, engaging tone that builds excitement and creates a sense of urgency without being pushy.
Use storytelling, clear analogies, and emotional appeals to connect with the reader and showcase the transformative power of the product.