Alex Morgan▫️ (@AlexMorgani7) header
Alex Morgan▫️ (@AlexMorgani7) profile picture

AI Educator 🚀 Helping you earn with AI, Tech Tools & Digital Skills DM open for collaborations📩

Joined January 2026
Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)Photo by Alex Morgan▫️ (@AlexMorgani7)
Seedance 2.5 looks insanely real. 👀🔥 The lip-sync, movements, lighting & details are on another level. 🤯 Coming soon to Higgsfield. 🚀 #Higgsfield #Seedance #AIVideo
🤝 Paid partnership
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Alex Morgan▫️ retweeted
🎉 BIG ANNIVERSARY GIVEAWAY! 🎂🔥 We're celebrating with $300 in prizes! 💰 🎁 3 lucky winners will receive $100 each! How to enter: ✅ Follow @TedCruz1072676 ❤️ Like this post 🔁 Repost to spread the word 🪙 Paid in your preferred crypto! ⏳ Giveaway ends in 48 hours. 🏆 Winners announced 72 hours after the original post goes live. Who's ready to win? 👀 Good luck, everyone! 🍀
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Alex Morgan▫️ retweeted
A quick reminder before the discounts disappear: CapCut Desktop Pro is 60% off and Ultra is 40% off, with October 30 as the last day. If I were making a Halloween campaign for an e-commerce brand, I'd show the product appearing in several unexpected settings to keep the video visually interesting. Design Studio can help me prepare supporting campaign visuals, while timeline editing lets me refine the product shots and make the video match the overall campaign look. CapCut Black Friday Sale: tinyurl.com/2v23rn22 #capcutpc #capcutmarketing #capcutblackfriday #capcutsale
🤝 Paid partnership
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Alex Morgan▫️ retweeted
I love a campaign idea that makes one product look different every time it appears. 👀 CapCut PC's Black Friday offer is ending October 30: 60% off Pro and 40% off Ultra. For creators who need to make several versions of a product promo, AI Edit can help get the first cut started. But I'd still review every scene, replace shots that don't show the product clearly, and adjust the transitions so the final video feels like one complete concept. Get the deal: tinyurl.com/2v23rn22 #capcutpc #capcutmarketing #capcutblackfriday #capcutsale
🤝 Paid partnership
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Alex Morgan▫️ retweeted
🚨 BREAKING: Claude can now design logos that look like they cost $10,000. I tested it myself. The final result cost me exactly $0. Here are the 7 prompts I used: Save this for later🔖
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Alex Morgan▫️ retweeted
You don't need expensive courses to start learning new skills: - Excel - Data Analysis - Data Science - Cyber Security Claude’s Learning Mode can help you understand complex topics and learn new skills for free. Here are 8 prompts to get started:
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Less time switching between editing tools. More time bringing creative ideas to life. DeeVid Al combines the essential steps of Al video production into one workflow. deevid.ai/app/ai-long-video
Turn Your Story into a Complete Video. 🎬 An all-in-one long-video workflow with no editing required. Create videos up to 30 minutes with: Script to Video Continuous Storytelling Consistent Characters Multi-modal Input AI Production Agent From story development and storyboarding to scene creation, voiceovers, and subtitles — everything in one workflow. Your story deserves to be told in full. Try Deevid AI Long Video #DeevidAI #AILongVideo #AIVideo #AIFilmmaking
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Alex Morgan▫️ retweeted
If Turing TTS encourages better human-baseline tests elsewhere, that would be a contribution even if another method eventually becomes the standard.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
POV: Your product ad got a little too ambitious and decided to break out of the frame. 😂 And while you're making your next creative masterpiece, don't miss 60% off CapCut Pro or 40% off CapCut Ultra. Black Friday deals end Oct 30, so grab yours before they're gone! Okay, this is the kind of visual that makes people look twice. You've got the giant portrait, someone is reaching in, the product reveal, and those close-up shots of the product itself. That's a lot of footage and visual elements to keep track of! CapCut PC's Multi-Track Editing lets you organise your clips, overlays and other assets on separate tracks, so you can adjust each layer without having to rearrange everything else. CapCut Sale: tinyurl.com/2v23rn22 #capcutpc #capcutmarketing #capcutblackfriday #capcutsale
🤝 Paid partnership
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Alex Morgan▫️ retweeted
I want human-like speech research to advance. I also want people to know when they are interacting with AI. Those positions are compatible.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
Your skincare product might look amazing on camera, but can viewers actually hear what you're saying about it? CapCut PC's Black Friday deal is on its final day: 60% off Pro and 40% off Ultra. For a UGC review with a voiceover, I'd use Edit Pilot to optimize the original audio, then use Enhance Voice if the spoken parts need more clarity. I'd also adjust the voiceover and music separately with Multi-Track Editing. tinyurl.com/2v23rn22 #capcutpc #capcutmarketing #capcutblackfriday #capcutsale
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Alex Morgan▫️ retweeted
How should a score above 50% be interpreted? Systematic misidentification is interesting, but it isn't the same thing as random guessing.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
A single engaging audio pair can explain the test. It can't substitute for the full evaluation.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Replying to @voicearena_ai
@voicearena_ai 's question isn't just how close are we. It's what exactly are we trying to get close to, and why?
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
The real potential of Al video isn't just making short clips. It's creating stories with a beginning, middle, and ending. DeeVid Al is exploring exactly that. deevid.ai/app/ai-long-video
Turn Your Story into a Complete Video. 🎬 An all-in-one long-video workflow with no editing required. Create videos up to 30 minutes with: Script to Video Continuous Storytelling Consistent Characters Multi-modal Input AI Production Agent From story development and storyboarding to scene creation, voiceovers, and subtitles — everything in one workflow. Your story deserves to be told in full. Try Deevid AI Long Video #DeevidAI #AILongVideo #AIVideo #AIFilmmaking
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Alex Morgan▫️ retweeted
Replying to @voicearena_ai
@voicearena_ai 's 94% figure is pooled across the evaluation. The best-model result is a different statistic. Keeping them separate matters.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
A strong Google result doesn't settle whether sounding human is what users need. Capability and product choice remain different decisions.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
The conversation should outlast the Google result. What does the next model teach us about human identification that this one doesn't?
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
A ranking can tell you who leads the tested group. Without a human comparison, it doesn't directly answer whether listeners can distinguish them from people.
Drop 2/15 Are we actually measuring the things we ultimately want our voice AI models to achieve? The best AI voices are becoming hard to tell apart. From each other. Not from humans. 🚀 Introducing Turing TTS: an evaluation that measures how often human listeners mistake AI-generated speech for real human speech. We tested leading TTS models against real human speech. Even the best model fooled listeners only ~10% of the time. With Turing TTS, we hope to contribute to a broader discussion within the research community about how we measure progress in voice AI. If one of our goals is to develop speech that is indistinguishable from human speech, how well do our current evaluation methods capture progress toward that goal? We don’t claim that Turing TTS is the right way forward, or that human indistinguishability should be the goal of every TTS system. Rather, we hope these findings encourage the community to collectively examine whether blind pairwise human evaluations of naturalness are sufficient, and what else we might need to measure. Results are now live on @voicearena_ai.
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Alex Morgan▫️ retweeted
Creating a complete Al film from a script sounds complicated, but DeeVid Al is making the workflow much simpler. Story development, video generation, voiceovers, subtitles, and editing in one place. deevid.ai/app/ai-long-video
Turn Your Story into a Complete Video. 🎬 An all-in-one long-video workflow with no editing required. Create videos up to 30 minutes with: Script to Video Continuous Storytelling Consistent Characters Multi-modal Input AI Production Agent From story development and storyboarding to scene creation, voiceovers, and subtitles — everything in one workflow. Your story deserves to be told in full. Try Deevid AI Long Video #DeevidAI #AILongVideo #AIVideo #AIFilmmaking
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Alex Morgan▫️ retweeted
A couple asked a sex therapist: "Our marriage is sexless. We haven't had sex in over four months. How do we turn this around and become passionate again?" The therapist smiled and said:
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