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- 🗣️ AI Streams Real-time Brain Speech?
Plus: The State of Software Quality Report
Read time: 5 minutes
Learning from the top names in AI? No fluff, no outdated theories - just real-world knowledge, and insights you won’t find in a textbook. Scroll down to know more!
What are on FIRE 🔥
IN PARTNERSHIP WITH BELAY
Accomplish More. Juggle Less.
When you love what you do, it can be easy to take on more — more tasks, more deadlines, more hours – but before you know it, you don’t have time to do what you loved in the beginning. Don’t just do more – do more of what you do best.
BELAY’s flexible staffing solutions leverage industry experience with AI systems to increase productivity without sacrificing quality. You can accomplish more and juggle less with our exceptional U.S.-based Virtual Assistants, Accounting Professionals, and Marketing Assistants. Learn how with our free ebook, Delegate to Elevate, and leave the more to BELAY.
AI REPORT
🤖 The State of Software Quality Report 2025
1. Meet the Hybrid Tester
Hybrid testers are the future. These professionals aren't just doing manual testing or relying solely on automation - they're blending human expertise with AI-driven automation to ensure software quality keeps pace with modern development. It’s a game-changer!
And guess what?
45% of high-maturity QA teams are already using automated regression testing.
37% are focusing on API testing. Hybrid testers are helping teams accelerate defect detection and optimize test coverage, while still ensuring human oversight.
2. AI's Huge Impact on QA
AI isn't just a buzzword in the QA world - 82% of respondents in the report say AI is critical to the future of testing. AI helps teams optimize test maintenance, detect defects faster, and boost testing efficiency.
In fact, teams using AI tools are 1.2 times more likely to invest in automation and have a more balanced documentation process.
3. Happiness = Better Testing
A happier QA team is a more effective one. In fact, happier testing professionals are 1.4 times more likely to have implemented advanced automation solutions. The moral of the story? Happy testers = high-quality software. Let’s keep that in mind when building your teams!
4. AI Adoption = Strategic Advantage
Teams embracing AI and automation are seeing big wins:
32% higher customer satisfaction
24% lower operational costs
11% faster time to market
It’s clear that the investment in AI isn't just for efficiency—it’s about making software quality a competitive advantage.
5. The Maturity Curve of QA
Here’s the thing: QA teams are at different maturity stages. According to the report:
26% of teams are still in the "Initial" stage, relying mostly on manual testing.
24% are "Managed", using basic automation for repetitive tasks.
25% have "Defined" processes, integrating moderate automation into critical workflows.
Only 14% and 11% have reached "Measured" or "Optimized" stages, where AI tools are a key part of the process.
Larger organizations (with >1,000 employees) are more advanced in their QA maturity, with 34% already using AI and extensive automation. But there’s still a lot of untapped potential to improve efficiency and quality across the board. 🚀
6. The Skills Hybrid Testers Need
To succeed, hybrid testers need a unique set of skills:
Automation scripting and programming are top priorities (68%).
API and web services testing is critical (43%).
And don’t forget about problem-solving and analytical skills (42%) - essential for tackling complex issues!
Interestingly, hybrid testers are 1.4 times more likely to prioritize AI and machine learning in their work, while focusing less on attention to detail compared to other testers. It’s about shifting to AI-powered test maintenance rather than manual verification.
7. Hybrid Testers = Time Savers
AI teams spend 28% of their time on automation, compared to 24% for non-AI teams
30% of AI-driven teams dedicate over 30% of their time to reporting, compared to 25% for non-AI teams.
Why it matters: In summary, the future of software testing is all about hybrid testers who use a mix of manual, automated, and AI-driven testing to ensure high-quality software. High-maturity teams are leading the way by adopting AI tools to optimize testing and speed up release cycles, all while improving customer satisfaction and reducing costs.
It’s an exciting time for QA professionals, and by embracing AI and hybrid testing, we can stay ahead in this rapidly evolving field.
TODAY IN AI
AI HIGHLIGHTS
🚀 Microsoft Fabric is a unified data platform used by 19,000+ organizations, including 74% of Fortune 500 companies. With AI and Copilot features, teams using paid Microsoft Fabric SKUs can now boost productivity and decision-making.
🧠 Researchers from UC Berkeley and UC San Francisco have developed a brain-to-voice neuroprosthesis that restores natural speech for those with severe paralysis, using AI to synthesize brain signals into real-time, fluent speech.
🤖 Alibaba is set to release Qwen 3, an upgraded AI model, possibly in April 2025. This follows the success of Qwen 2.5-Max, launched to compete with DeepSeek-V3 amid fierce competition.
🔎 DeepMind has tightened its research release process, implementing a six-month embargo on key papers, especially those on generative AI, to avoid giving competitors an advantage and protect Gemini's reputation.
🗣️ There's a new voice in ChatGPT. This voice perfectly captures the mood of an employee on a Monday. Imagine talking to AI with this voice on a Monday - oh, it might make me quit my job! Just for fun.
No joke, there's a new voice in ChatGPT.
— OpenAI (@OpenAI)
5:33 PM • Apr 1, 2025
🚀 OpenAI just launched OpenAI Academy! This free platform offers tons of content, including videos and events, to help you learn any AI knowledge or skill. With dozens of hours of content, it's a great resource for all!
💰 AI Daily Fundraising: Temporal, a Seattle-based company, raised $146 million to expand into AI and agentic AI microservices. With a valuation of $1.72 billion, it aims to grow its platform and develop AI use cases.
AI SOURCES FROM AI FIRE
NEW EMPOWERED AI TOOLS
👨🏻💻 Transform how you work in Google Workspace. Automate busywork and create faster in Google Docs, Sheets, and Gmail with GPT Workspace. Save hours every week without leaving your favorite tools. Try Now For Free*.
🎥 Ray2 Luma Camera Motion Concepts 20+ cinematic camera motions for smooth control
💬 Keyword Research Tool is a quickly research keywords with no sign ups or payments
🖼️ OctoComics is an AI-powered comic generator with a creative community
📸 SnapGrid is an Open-source app for organizing and analyzing UI screenshots
*indicates a promoted tool, if any
AI QUICK HITS
🤖 Zhipu AI Joins Competitive China AI Race with Free Agent (Link)
🍏 Apple Introduces Apple Intelligence for Vision Pro (Link)
📈 AI Augmentation Boosts High Performers More Than Low-Skilled (Link)
🚪 Joelle Pineau Departs Meta's AI Research Team (Link)
📚 OpenAI Accused of Using Paywalled O'Reilly Books for Training (Link)
AI INSIGHTS
An AI bubble threatens Silicon Valley, and all of us.
OpenAI’s been making huge moves - $500B Stargate supercluster, massive AGI promises, and raising cash like it’s running out of oxygen. But here’s the catch: they’re losing two dollars for every one they make. Even with $3.7B in revenue last year (2024), they expect to burn $11B in 2026. And they say they'll only break even at $100B/year - on par with companies like Nestlé.
Meanwhile, DeepSeek R1 (yep, that open-source model from China) just matched OpenAI’s flagship performance - for 95% less cost. It’s like someone dropped the same iPhone… but free. Unsurprisingly, this spooked investors. Nvidia lost $600B in market cap in a single day after the R1 news dropped.
And yet, VCs and Big Tech are going all-in. Over $200B in VC money has flooded AI since 2021. Big Tech spent $246B in 2024 alone. Goldman Sachs says it’ll cross $1 trillion in the next 5 years. All for models that, as studies show, often don’t even boost productivity. Engineers using Copilot? No measurable gains. Microsoft even found that people relying on AI tools stop thinking critically.
Now add this: running these models eats a ridiculous amount of power. OpenAI wants five-gigawatt data centers. McKinsey says AI alone could consume up to 12% of U.S. electricity by 2030—three times today’s levels. Utility companies may need to drop another $500B just to keep up.
And the market? Totally hooked. The “Magnificent Seven” (Apple, Nvidia, Meta, etc.) drove 71% of the S&P 500's 2023 gains. But that means if AI demand dips—even a little - the fall could be brutal. It’s all starting to resemble the dot-com bubble or worse... the 2008 housing crash.
OpenAI is betting on AGI to justify its costs. But with open models like R1 outpacing them on price and performance, it’s fair to ask: is this sustainable, or are we watching another bubble inflate?
Let me know what you think: are we in too deep, or just getting started?
AI JOBS
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