Adiyan🌼 (@Adiyan_coder0) header
Adiyan🌼 (@Adiyan_coder0) profile picture

Helping Founders & CEOs build authority and grow their personal brand on LinkedIn & X | AI, Tech & Innovation | Open for Paid Collaborations📩

Australia
Joined March 2024
Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)Photo by Adiyan🌼 (@Adiyan_coder0)
Your next AI video project deserves room to grow. With Flova 1.5, purchase one year of Pro and receive another year free during the launch promotion. Seedance 2.5 720p starts at $0.025/sec. flova.ai/?refCode=3BFU8P57
Have you checked out the Flova 1.5 Launch Special yet? Get 2 years of Pro for the price of 1! Keep the extra year or gift it to someone special. Seedance 2.5 720p from just $0.025/sec! ⏰ Limited time only. Ends Nov 30!
9
9
10
962
Adiyan🌼 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.
11
15
15
441
Adiyan🌼 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.
10
13
13
307
Adiyan🌼 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.
13
15
15
314
Adiyan🌼 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
16
16
17
3,791
Adiyan🌼 retweeted
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.
13
14
14
234
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.
11
13
12
365
Adiyan🌼 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.
11
13
12
365
Adiyan🌼 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.
18
14
14
278
Adiyan🌼 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
24
17
17
5,905
Adiyan🌼 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.
12
14
14
299
Adiyan🌼 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
13
16
16
511
Adiyan🌼 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.
12
13
14
138
Adiyan🌼 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
18
20
20
204
Adiyan🌼 retweeted
We’ve raised $1.3M from YC & Afore Capital so you never have to type or speak again. Typing is slow. Talking into your computer is awkward. Subvocal fixes both Our glasses give you the speed of speech without you making a sound or touching a keyboard. It tracks your internal speech muscles with non-contact sensing and decodes silent, almost invisible mouthing into text at more than 200 words/min. Pre-orders are now live at: subvocal.co/preorder?utm_sou…
1,315
1,372
1,330
13,522
6,979,176
Adiyan🌼 retweeted
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.
213
92
242
474
403,248
Adiyan🌼 retweeted
Your iPhone has a hidden setting that can make your Wi-Fi work better. And most people never touch it. Here are 7 Wi-Fi settings you should check tonight:👇
15
31
32
710
Adiyan🌼 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:
37
55
63
6,938
Adiyan🌼 retweeted
30 Websites That Feel "Illegal" But Are Perfectly Legal 1. raphael.ai — Free unlimited AI image generation, quality rivals Midjourney 2. krea.ai — Real-time AI image generation, draws as you go 3. magnific.ai — AI unlimited image upscaling, details auto-filled 4. clipdrop.co — AI one-click background removal/lighting fix/erasure 5. elevenlabs.io — AI voice cloning, mimics any voice in 5 seconds 6. suno.com — Input lyrics to auto-generate full songs 7. runwayml.com — AI video generation pioneer, free Gen-3 trial 8. klingai.kuaishou.com — Kuaishou Keling AI, smoothest Chinese video generation 9. d-id.com — One photo + one audio clip = talking digital human 10. sadtalker.ai — Turns static photos into talking videos 11. cursor.com — AI code writing, free quota enough for daily use 12. bolt.new — Build websites by talking, zero code 13. v0.app — Vercel AI frontend generator, description becomes page 14. replit.com — Code in browser + AI assistance + one-click deploy 15. napkin.ai — Paste text to auto-generate infographics 16. gamma.app — AI one-click PPT generation, say goodbye to PPT hell 17. notion.com/product/ai — Notion AI for writing, summarizing, translating 18. uizard.io — Sketch a drawing, AI generates real webpage 19. perplexity.ai — AI search engine, answers any question instantly + sources 20. phind.com — Developer-exclusive AI search, code issues solved on search 21. otter.ai — Real-time meeting transcription, free 300 minutes monthly 22. opus.pro — AI short video editing, auto-finds highlight clips 23. poe.com — One site to use GPT-4o / Claude / Gemini 24. huggingface.co/spaces — Open-source AI model free playground 25. remove.bg — One-click AI background removal, 1-second output 26. cleanup.pictures — AI erases any object from photos 27. deepswap.ai — AI face swap, 1-minute turnaround 28. musiio.com — AI music tagging + recommendations 29. jasper.ai/free — AI writing assistant, free version enough for daily use 30. claude.ai — Anthropic free AI assistant, top-tier long-text handling Follow for more information @hey_Jessicaai
28
39
51
1,781
Adiyan🌼 retweeted
🚨 BREAKING NEWS: CHATGPT can now create a full YouTube channel for you using AI, like an agency that generates $10,000 a month. Free. Here are 7 prompts to go from 0 → monetized channel in 90 days:
23
33
45
735