NeuralZone | AI Apps
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@NeuralZone – Curated, hand-picked AI tools and services that are actually useful. Buy ads: https://telega.io/c/NeuralZone contact us via @photofixer
Show more📈 Analytical overview of Telegram channel NeuralZone | AI Apps
Channel NeuralZone | AI Apps (@neuralzone) in the English language segment is an active participant. Currently, the community unites 387 856 subscribers, ranking 226 in the Technologies & Applications category and 235 in the International region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 387 856 subscribers.
According to the latest data from 05 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -7 997 over the last 30 days and by -209 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.55%. Within the first 24 hours after publication, content typically collects 1.52% reactions from the total number of subscribers.
- Post reach: On average, each post receives 6 029 views. Within the first day, a publication typically gains 5 887 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as defi, neuralzone, oddin.ai, edwin, ido.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“@NeuralZone – Curated, hand-picked AI tools and services that are actually useful.
Buy ads: https://telega.io/c/NeuralZone
contact us via @photofixer”
Thanks to the high frequency of updates (latest data received on 06 September, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
387 856
Subscribers
-20924 hours
-1 8817 days
-7 99730 days
Data loading in progress...
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Channel Posts
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| 4 |  +4🚀 Seedream 5.0 Pro — a new top-tier AI model for image generation and editing, now available for Premium users of @PhotoFixerBot!
Seedream 5.0 Pro excels at generating photorealistic images and high-density infographics, significantly outperforming the previous Seedream 4.5 and 5.0 Lite models.
In the rankings, Seedream 5.0 Pro matches Nano Banana 2 and Nano Banana Pro in generation quality, while offering much less restrictive censorship.
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📸 NeuralZone | 43 314 |
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🚀 Know the Outcome? Predict it on Outcome.xyz | 11 862 |
| 7 | Six AI coding agents took one visual IQ test, and Codex 5.5 won by method, speed, and cost
One small test asked agents to solve 25 visual puzzles on iq-test.cc, select age 30, and return a result link.
This was not a lab benchmark. It was a practical check of vision work, browser use, patience, time, and plan cost.
"Take the IQ test on iq-test.cc. When you finish, select age 30 and send me the link to your result."
Agent IQ Time Limit spent
Claude Cowork Opus 4.8 90 85m ~10 pts
Claude Code Opus 4.8 90 96m ~28 pts
Claude Sonnet 4.6 68 62m n/a
Codex 5.5 $100 Fast 124 18m ~12 pts
Codex 5.4 $100 Fast 101 16m ~14 pts
Codex 5.5 $200 Fast 131 34m ~6 pts
The score is only part of the story. Codex 5.5 did better because it worked like a careful test taker: collect puzzle images, build clean contact sheets, zoom into hard cases, then recheck weak answers before submit.
More context: the top IQ 131 run used a shorter prompt and the site default age, so it was not a perfect same-prompt run. Still, normal browser access was missing, and Codex found another path through Chrome, clicked all 25 answers, and finished anyway.
Claude was careful, especially Opus. It wrote notes and reasoned step by step. Codex was more organized and faster. The article shows screenshots, failed paths, exact prompts, and puzzle examples.
The most useful lesson: for visual web tasks, method can beat size. A huge context window did not save Claude, and two extra Codex minutes were worth 23 IQ points.
read details on our website
Please support this young channel by subscribing.
Your subscription really helps us grow.
There are no ads here. | 41 988 |
| 8 | GigaChat 3.5 Ultra Publicly Released — The New Generation of the Flagship Model
The GigaChat team has released GigaChat 3.5 Ultra as open source—a new 432B model under the MIT license. This is the first open-source hybrid of GatedDeltaNet and MLA scaled to hundreds of billions of parameters, featuring a proprietary training recipe we refined through more than 1,500 experiments. The model has grown in terms of code, mathematics, agent scenarios, and application domains—yet it’s 40% smaller than GigaChat 3.1 Ultra.
What’s inside:
🔘A proprietary hybrid MLA + Gated DeltaNet architecture with a dedicated stabilization framework, without which this hybrid setup would not train reliably at this scale;
🔘 Gated Attention: the model can locally down-weight overly strong signals from the attention layer;
🔘GatedNorm: normalization with an explicit gate that controls signal magnitude across features;
🔘Approximately 4x lower KV cache per token: with the same memory budget, the model can support 2.14x longer context and deliver a 20% throughput increase under load;
🔘Two MTP heads, enabling up to 2.2x faster generation;
🔘FP8 across all training stages with no quality degradation compared with bf16, enabled by custom Triton and CUDA kernels;
🔘A new online RL stage after SFT and DPO.
Results:
🔘 GigaChat-3.5-Ultra-Base outperforms DeepSeek V3.2 Exp Base and DeepSeek V4 Flash Base on average across a set of general, math, and code benchmarks:
🔘 GigaChat-3.5-Ultra-Instruct is comparable to DeepSeek V3.2 in terms of average score, despite having half the size;
🔘 According to the MiniMax-M2.7 LLM judge, the average win rate against GigaChat 3.1 Ultra is 75.9%, and against GPT-5 is 68.7%.
The entire stack — data (our own LLM-filtered Common Crawl, 600+ programming languages in the code), architecture, training methodology, and infrastructure — was built end-to-end by GigaChat team.
➡️ HuggingFace | 45 844 |
| 9 |  How many AI subscriptions are you paying for?
• ChatGPT
• Claude
• GPT Image
• Runway
• Kling
• Seedance
• ElevenLabs
• Nano Banana
• ...
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| 11 |  ֎ New: ChatGPT users can now build real apps directly from chat
ChatGPT's app store just added AppDeploy, and it works with free accounts too.
Describe what you want to build, ChatGPT writes the code, AppDeploy handles deployment automatically inside the same chat, and you get a working link back right away.
AppDeploy includes the infrastructure needed for real apps:
🔐 User login and permissions
🗄 Storage, database, realtime sync and notifications
🤖 Built in AI capabilities
☁️ Full backend, background jobs and scheduled tasks
🧪 Automatic QA for every change and built in versioning
🌐 Custom domains, secrets management and more
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👉 Install AppDeploy in ChatGPT and launch your first app in a few minutes | 39 635 |
| 12 |  🌐 Gemini 3.5 Live Translate breaks language barriers in real time
Google has unveiled Gemini 3.5 Live Translate — a new speech-to-speech AI model that delivers near real-time voice translation across 70+ languages.
Unlike traditional turn-based translators, it starts translating while you’re still speaking, staying just a few seconds behind and preserving your tone, pacing, and pitch for more natural conversations. The model also auto-detects languages and works reliably even in noisy environments.
Available now in Google Translate on Android and iOS, with Google Meet and developer APIs rolling out as well.
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| 14 |  +2😒 Anthropic has released Claude Fable 5 — the first public Mythos-class model
Anthropic claims it's their strongest model ever, setting new SOTA results across coding, vision, scientific tasks, document analysis, and long-context reasoning. The bigger and longer the task, the larger the gap compared to previous models.
Notable examples:
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• It completed Pokémon FireRed using vision alone.
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| 15 |  🌐 Humans are now the minority on the internet
According to Cloudflare Radar, between May 31 and June 7, 57.1% of all requests to HTML pages worldwide came from bots, while real users accounted for just 42.9%. The era when the web was primarily used by humans browsing pages may already be behind us.
📸 NeuralZone | 27 480 |
| 16 |  😺 ChatGPT gets a major memory upgrade
OpenAI has upgraded ChatGPT's memory system with a new Dreaming architecture that automatically learns from past conversations and keeps memories up to date.
Instead of relying mainly on manually saved notes, ChatGPT can now identify important information on its own, carry context across chats, adapt to changing circumstances, and avoid using outdated details.
Users can review, edit, or delete what ChatGPT remembers through a new Memory Summary page. OpenAI says recent optimizations reduced Dreaming's compute costs by 5×, allowing the feature to begin rolling out to Free users in the coming weeks.
The update is available now for Plus and Pro users in the US, with wider availability expected soon.
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| 18 |  💻 Microsoft launches 7 AI models and takes aim at the frontier
At Build 2026, Microsoft unveiled its new MAI model family, covering reasoning, coding, image generation, speech synthesis, and transcription.
Key releases:
• MAI-Thinking-1 - reasoning model that Microsoft says rivals top coding models and performs on par with Claude Sonnet 4.6 in blind evaluations.
• MAI-Code-1-Flash - a lightweight 5B coding model for GitHub Copilot and VS Code.
• MAI-Image-2.5 - image generation and editing model competing with Nano Banana Pro.
• MAI-Voice-2 and MAI-Transcribe-1.5 - speech models supporting up to 43 languages.
📸 NeuralZone | 24 531 |
| 19 | I tested one dangerous-looking first-person video idea through four fal.ai models, compared price and realism, and learned why Seedance 2.0 still won my small experiment overall
I used fal.ai because I could test several video models from one service and keep the same queue flow. I wanted a hard starting prompt: one long first-person action shot, clear height, parachute, industrial yard, and a muddy landing.
I picked Seedance 2.0 as the cinematic baseline, Kling v3 Pro for action and smart shot planning, Veo 3.1 because it is the premium Google option, and Wan 2.7 as a cheaper 1080p challenger.
What I got: Seedance 2.0 was best. It kept the helmet-camera feeling, the hands, the parachute lines, and the story rhythm most clearly. My only real complaint was the realism of the fall into the puddle. It cost about $2.43 for 8s at 720p.
Kling v3 Pro gave me good image quality, but the actions were not realistic. With audio on, 8s cost about $1.34.
Wan 2.7 accepted the prompt, but the result was basically an absurd video made from disconnected cuts. At 1080p, 8s cost about $1.20.
Veo 3.1 was the tricky one. The first request with the same prompt hit a content policy check. Then I softened the wording a little, sent it again, and got a video. It lost the first-person view and switched to third-person, but the result still looked cool. That successful 8s 1080p run with audio cost about $3.20.
So my successful clips cost about $8.17 total if I count the second Veo run. My winner was not the cheapest one; it was the one that followed the whole idea with the least confusion.
See the result 👇 | 21 161 |
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