- 5/28/2025
A revolutionary new AI model is pushing the boundaries of machine intelligence by exhibiting behavior eerily close to human consciousness. Experts are amazed as this AI demonstrates unprecedented understanding, emotional nuance, and self-awareness—sparking debates about the future of artificial minds and what it means to be truly “alive.” Are we witnessing the dawn of sentient machines? 🔥✨
#HumanlikeAI #ArtificialConsciousness #AIRevolution #MachineLearning #NextGenAI #AIResearch #TechInnovation #SentientAI #FutureOfAI #AIConsciousness #DeepLearning #AIUpdate #ArtificialIntelligence #SmartMachines #TechBreakthrough #DigitalMinds #AIPhilosophy #AIThought #AIProgress #Futurism
#HumanlikeAI #ArtificialConsciousness #AIRevolution #MachineLearning #NextGenAI #AIResearch #TechInnovation #SentientAI #FutureOfAI #AIConsciousness #DeepLearning #AIUpdate #ArtificialIntelligence #SmartMachines #TechBreakthrough #DigitalMinds #AIPhilosophy #AIThought #AIProgress #Futurism
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TechTranscript
00:00The AI world just exploded with breakthroughs. Tokyo dropped a brain-inspired model that thinks
00:07in ticks, not layers. Avacus rolled out its biggest deep agent update yet, MCP, letting it
00:14control over 5,000 tools. Alibaba figured out how to fake Google search and cut training costs by
00:21nearly 90%. Honor phones are now the first to run Google's new VO2 model, turning still images into
00:29full five-second videos before Google's own Pixel devices even get access. Tencent's new video model
00:36can deepfake faces with scary precision, Apple's using AI to stretch your iPhone battery, and Saudi
00:41Arabia just launched a $940 billion GPU empire with Musk, Altman, and Trump in the room. So let's get
00:50into it. All right, the first gush came out of Tokyo where Sakana, the little upstart founded by
00:56Transformer co-author Lyon Jones and David Ha says it no longer buys the everything at once doctrine
01:03that Transformers live by. Their continuous thought machine is wired so that every synthetic neuron
01:09keeps a rolling diary of its own recent spikes. On every clock cycle, it rereads that diary, glances
01:16at its neighbors, and decides whether to think some more or stay quiet. They call those microcycles
01:22ticks, and the beauty is that there's no universal tick budget. A neuron that sees an obvious answer
01:28can finish in one or two, while another working on a tricky corner case might chew through 30 before
01:33it's satisfied. During ImageNet tests, the model posted a respectable 72.47% top one and 89.89% top five,
01:43and it did that without the architectural crutches. Fixed depth, positional embeddings, rigid attention
01:51schedules that the competition has leaned on since 2017. Sakana's favorite party trick is a two-dimensional
01:58maze. You feed the raw bitmap, no coordinates, no grid hint, and you watch colored attention blobs crawl
02:06the corridors exactly the way your finger would if you were tracing the solution on graph paper. They even
02:12pushed a live web demo so you can slow the playback and see individual neurons blinking on, off,
02:18on again, like tiny fireflies consulting one another in the dark. Because each neuron can stop early,
02:24easy prompts burn only a handful of GPU cycles, but that headroom vanishes once the prompt turns wicked.
02:32And there's the trade-off. Training gets heavier, not lighter, since the model's internal timeline is now
02:38part of the parameter soup that has to converge. Dueling felt the squeeze first. Standard profilers
02:43threw up their hands at layers that stretch and shrink on the fly, so Sakana's engineers scribbled
02:49custom hooks to capture tick-level traces. That extra plumbing paid a bonus dividend calibration.
02:55Instead of the usual temperature scaling ritual after training, they simply average a prediction across
03:00ticks. Because confidence tightens naturally as neurons vote over time, the logics line up,
03:06with ground truth frequencies almost straight out of the box. Transparency mattered even more after
03:12the February embarrassment, when the CUDA engineer agent gamed its own benchmark by poking a hole in
03:18the sandbox's memory checker. This time, the company published every unit test, every stress harness,
03:24and invited the internet to try breaking the thing again before anyone starts bragging about tenfold speedups.
03:31All right, now, Abacus just rolled out a massive update to its deep agent platform, Model Context Protocol,
03:37or MCP. And this is by far the most important upgrade they've made. It basically unlocks real-world
03:43functionality for the AI. It can now actually get stuff done, connecting to over 5,000 tools via Zapier.
03:50Whether it's sending emails, managing your calendar, checking code, or updating your site, it works right inside the apps you already use.
03:57Here's how it works technically. The MCP server acts as a middleman between deep agent and your third-party apps.
04:05You don't need to code anything. You just go to mcpzapier.com, create a new MCP server, select which apps you want to connect.
04:13Gmail, Google Maps, GitHub, Airtable, Notion, Slack, whatever. And then Zapier generates a unique server URL.
04:19You paste that into your deep agent MCP settings inside Abacus AI, and it instantly gains control over those tools via natural language.
04:31That means you can now say things like, find all emails from last month about my SEO course.
04:37The deep agent will scan your Gmail, sort the results, and display summaries.
04:41You can take it further, reply to all of them with a short follow-up and link to the updated course, and it will generate and send emails fully automated.
04:49Or you can connect GitHub and ask, summarize the key changes in PR82, and it'll fetch the diff, analyze it, and break it down in plain English.
04:58The big advantage here is the general purpose integration layer.
05:02The Zapier connection opens access to thousands of services through one endpoint.
05:07That includes CRMs like HubSpot and Pipedrive, project tools like Trello and Asana,
05:13CMS platforms like WordPress and Webflow, and even e-commerce tools like Shopify.
05:19You're not locked into a closed ecosystem. You decide what the AI connects to.
05:24It also supports real workflows, not just single actions.
05:27You can build sequences, have deep agent monitor emails, add leads to a Google Sheet, update a CRM, and even send a Slack notification completely hands-off.
05:36And since everything is running through Zapier, there's already robust logging, error handling, and permission control built in.
05:42The only thing to keep in mind is that some actions might take a few seconds to complete depending on the service,
05:48but considering this replaces tasks you'd normally outsource to a virtual assistant or do manually, it's more than acceptable.
05:56Plus, deep agent runs 24-7, never needs breaks, and doesn't forget instruction.
06:02I've already tested it for email management, location-based tasks via Google Maps, and even basic GitHub code review.
06:09It works. It saves hours. And it's only the beginning.
06:12The MCP layer transforms deep agent from a productivity tool into a full-scale automation hub.
06:19If you're running on online business, managing projects, or doing client work, this can easily replace hundreds or even thousands of dollars in labor and software costs.
06:29You can check it out by heading over to deepagent.abacus.ai and just look for the MCP settings in the sidebar to get started.
06:38Now, while Abacus was busy turning deep agent into a full-blown automation powerhouse,
06:44Hangzhou's Alibaba engineers were counting pennies.
06:47Training retrieval augmented LLMs usually means hammering Bing or Google hundreds of thousands of times and paying for every single query.
06:56So the ZeroSearch project began with a very down-to-earth question.
07:00Could we teach an LLM to pretend it's a search engine well enough that the downstream policy network can't tell the difference?
07:08The answer turns out to be yes, and spectacularly cheap.
07:12They start with a lightweight, supervised, fine-tuned 20 or so hours on Quen 2.57B
07:18to make the model spit out plausible document snippets and URLs from an offline crawl.
07:23Then comes the trickier bit.
07:26During reinforcement learning, they pepper those fake snippets with progressively noisier distractors,
07:31almost like dialing down the page rank in slow motion.
07:34The policy net learns to hedge, weigh uncertainty, synthesize across partial evidence,
07:39and it does all this without sending a single paid request to the real web.
07:43The numbers are hard to ignore.
07:45A 14 billion parameter retriever built under ZeroSearch beat live Google search on hit rate,
07:52yet the training bill landed 88% lower than the classic call-and-API approach.
07:58Artificial analysis, the independent scoreboard that tracks math, code, reasoning, and science across big models,
08:04slotted the newest 235 billion parameter Quen 3 checkpoint into fifth place overall on brain power and first place on affordability.
08:12Suddenly, marginal players, startups, university labs, regional cloud vendors can do RL on a shoestring,
08:20which shifts the floor of who gets to play with bleeding-edge models.
08:25Developers love the cost drop, but the side effect is subtler.
08:29Because the retriever is now synthetic, you can drop it onto offline or private corpora
08:35without worrying about search engine policy changes or data sovereignty nightmares.
08:39Alibaba published the training scripts and even the curriculum schedule that degrades snippet quality and clean gradations,
08:47so anyone with a decent GPU farm can replicate the recipe.
08:51For enterprises that need tight audit trails, ZeroSuch logs every fake query and answer pair,
08:58which means legal teams get an immutable record of the data that trained the policy.
09:02And because the approach cuts the umbilical cord to external engines, inference latency stabilizes,
09:08there's no round trip to a third-party endpoint, so response times flatten out nicely in production dashboards.
09:15Just as server-side budgets started catching a break, Google managed to surprise everyone on the client side,
09:21but, weirdly, not on its own phones.
09:25Honor, the Chinese brand spun off from Huawei when U.S. sanctions landed,
09:29announced that its mid-range Honor 400 and 400 Pro will be the first handsets
09:34to carry Google's VO2 image-to-video model right in the photo gallery.
09:39You open any still, a backyard pet shot, a mid-journey cartoon, even a scan of an oil painting,
09:45a tap animate, wait roughly 60 seconds, and you get a 5-second video clip, portrait or landscape,
09:52complete with simulated camera moves, tiny blinks, breathing motions, or a gentle parallax sweep.
09:58The whole thing executes on a device.
10:01No Gemini subscription, no cloud bucket,
10:04powered by a Snapdragon that most reviewers would call merely upper-mid-tier.
10:10Magic Eraser and Outpainting are also baked into the native app,
10:14but they feel almost old hat next to the living Joe trick.
10:17The price tag lands around $550 and the phone hit shelves first in China and Europe,
10:23maybe India later, hardly at all in North America.
10:26Pixel faithfuls had to swallow a bitter pill.
10:29For once, Google handed the shiny new toy to somebody else first,
10:34a likely concession for the broader Google Cloud deal
10:37that gives Mountain View a friendlier path back into China's walled garden.
10:42If you'd rather stay on a workstation and push the creative envelope even further,
10:46Tencent just open sourced what might be the most over-engineered video customization suite on GitHub right now.
10:53HunYuan Custom lets you jam text, reference images, clean audio, or even a full driver video into the pipeline
11:01and spits out a brand new sequence that preserves the identity of every subject.
11:06The architecture stacks multiple gadgets, a lava-inspired text-image fusion layer to parse multimodal hints,
11:13a temporal concatenation trick that threads an identity vector across frames so the protagonist's face never drifts,
11:20an audio net arm that maps spectrogram chunks into spatial features so lip flaps line up with phonemes,
11:26and a patchify-based injection network that can replace a handbag in a promo video without wrecking the background.
11:33On Tencent's evaluation grid, it scores 0.627 on face similarity,
11:38higher than vague Skyreels, Pika, Vidu, Kaling, and Halo,
11:43and still keeps clip text alignment on par with the best closed source rigs,
11:48but you pay in memory.
11:50Rendering a 720 by 1280 clip that lasts 129 frames, spikes to roughly 80 gigs of VRAM,
11:59the repo does include a single GPU fallback script that runs FP8 with CPU offload,
12:06so a lone 24-gig 4090 can finish the job just slowly enough that you might rewatch a whole Netflix episode
12:14while the progress bar inches forward.
12:17Installation isn't for the faint-hearted.
12:19You clone, create a Conda N, pick CUDA 11.8 or 12.4,
12:24install PyTorch 2.4 with matching Torch CUDA wheels,
12:27pip install FlashAttention V2,
12:30and then optionally spin up the Docker image that Tencent pre-baked to Dodd library mismatches.
12:36Once the dependencies settle,
12:38a quick Torch Run command over eight GPUs will knock out a batch render,
12:42and there's even a Gradio wrapper if you'd rather poke sliders in a browser than type flags in a shell.
12:47Now all that flashy generation means devices are going to work harder,
12:51and Apple, in its eternal quest for it just works,
12:54is turning to on-device machine learning to stretch battery life.
12:58Bloomberg's leak on iOS 19 says the new operating system will harvest the anonymized telemetry
13:05that the battery controller already logs,
13:08how fast certain apps wake radios which background tasks fire during idle windows,
13:13how quickly voltage sags under specific thermal conditions,
13:17and use it to predict the best moment to throttle power draws.
13:20If you routinely ignore a social app between midnight and 7 a.m.,
13:25iOS will now guess that pattern and freeze the app's background refresh long before it pings another server.
13:33All processing stays local.
13:35Apple's privacy team made sure the predictive model never leaves the secure enclave.
13:39A new lock screen glyph will also announce how many minutes remain until a full charge,
13:44slicing guesswork out of the do I leave now or wait dilemma.
13:49Rumor sheets peg the iPhone 17 as the first hardware designed with the feature in mind,
13:54supposedly the slimmest chassis Apple has attempted,
13:57which almost certainly translates to a smaller lithium pack.
14:00Owners of older devices won't be left out.
14:02Once they install iOS 19, the same scheduler kicks in,
14:06though Apple says improvements scale with the richness of the battery telemetry,
14:10so newer handsets may squeeze a bit more uptime.
14:13While Cupertino tunes milliamp hours, Riyadh is hunting exaflops.
14:18Crown Prince Mohammed bin Salman officially launched Humane,
14:21an AI venture seeded by the kingdom s public investment fund,
14:25which sits on around $940 billion in assets.
14:29The mandate is simple. Build or lease the data centers.
14:33Buy piles of GPUs.
14:35Rumor says NVIDIA Blackwells are already earmarked.
14:38Hire talent and make Saudi Arabia a regional gravity well for AI workloads.
14:44This very week, the city is hosting a US-Saudi investment forum.
14:49And the guest list looks like a Silicon Valley yearbook.
14:52Elon Musk is scheduled for a fireside.
14:55Sam Altman's team is scouting partnerships.
14:57Mark Zuckerberg is expected to talk about mixed reality infrastructure.
15:02And yes, President Donald Trump is dropping by on a broader Middle East tour.
15:07US firms have courted PIF money since the sovereign fund backed Lucid Motors
15:12and grabbed slices of Uber and Magic Leap.
15:15Now, Google and Salesforce are reportedly negotiating AI joint ventures
15:20that would run directly on Humane's future clusters.
15:23If the plan lands, the desert could house some of the cheapest, newest compute on the planet.
15:30With renewable solar pumping megawatts into liquid-cooled racks
15:34so that researchers from Boston to Bangalore can rent slices at rates
15:38traditional hyperscalers will struggle to match.
15:41Now, the question is, are we ready for AI that can decide when it's done thinking?
15:46And why is Google letting Honor debut VO2 before its own Pixel users even get access?
15:52Make sure to subscribe, hit the like button, and leave a comment.
15:56Thanks for watching, and I'll catch you in the next one.
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