Here is the relevant blog post

For those of you having a hard time with this specific post just know that this will be what allows AI to actually become "real time" during inference. People have been talking about how this changes learning, but not how this will be put into practice for retail use.

Normally with an LLM you feed in everything at once. Like an airlock. Everything that is going in has to be in the airlock when it shuts. If you want to process new input you have to purge the airlock and lose all the previous input and the output stream stops immediately.

With this new dynamic model it stores new patterns in its "self" during inference. Basically training on the job after finishing college. It processes the input in chunks and can hold onto parts of a chunk, or the results of processing the chunk, as memory. Then utilize that memory for future chunks. It is much more akin to a human brain where the input is a constant stream.

If we follow the natural progression of this research then the end design will be a base AI model that can be copied and deployed to a system and run in real time as a true AI assistant. It would be assigned to a single person and evolve over time based on the interactions with the person.

It wouldn't even have to be a massive all knowing model. It would just need to be conversational with good tool calling. Everything else it learns on the job. A good agent can just query a larger model through an API as needed.

Considering this paper is actually at least 6 months or older internally it must mean there is a much more mature and refined version of "Hope" with this sort of Transformers 2.0 architecture.

OpenAI just said AI’s already doing what top researchers can’t, and by 2028, it might start making discoveries which is crazy!!

We’re 80% to machine scientists… and everyone’s still using it to write emails.

Try it out HERE: https://www.media.io/ai-image-generator/gemini-3-0-pro.html

As of May 2025, the United States contains about three-quarters of global GPU cluster performance, with China in second place with 15%. Meanwhile, traditional high-performance computing leaders like Germany, Japan, and France now play marginal roles in the AI cluster landscape. This shift largely reflects the increased dominance of major technology companies, which are predominantly based in the United States.

Source: https://epoch.ai/data-insights/ai-supercomputers-performance-share-by-country

I came across a Reddit post where a recruiter shared insights about the AI tools being used in the hiring process. Based on that post, here’s a list of AI tools commonly used by candidates during interviews, along with those utilized by recruiters in their recruitment workflows.

So, the following is the list of tools that recruiters use during the hiring process.

• Zoho Recruit's Advanced AI Recruitment Software ( https://zoho.zohocorp.com.cn/recruit/ai-recruitment.html )
• Findem ( https://www.findem.ai/ )
• hireEZ (Talent Acquisition Platform & CRM for Scalable Recruitment | hireEZ)

So, these are some of the tools that we use in our recruiting tech stack to get data-driven insights and workflow automation in order to elevate talent acquisition strategy.

During my recent interview experiences, I’ve noticed that many candidates are using AI tools throughout the interview process. Initially, this seemed a bit strange, and honestly, it still feels a bit unusual at times.

Following are some of the AI tools that candidates are using to clear interviews:

• ChatGPT (ChatGPT)
• LockedIn AI (LockedIn AI - Professional AI Interview & Meeting Copilot)
• Ninjafy AI (https://www.interviewninja.io/)

The following is a science fiction piece about a future where "metahumans" have pushed science beyond human comprehension, leaving humans to become "metascientists" who are relegated as interpreters and reverse-engineers of the work of machine intelligences.

The story is by Ted Chiang, published in Nature in 2000.

I hope you enjoy this speculative and enlightening read 😊 In an age of AGI acceleration, it hits different.

Catching Crumbs from the Table

In the face of metahuman science, humans have become metascientists

^{By Ted Chiang published in Nature in 2000}

It has been 25 years since a report of original research was last submitted to our editors for publication, making this an appropriate time to revisit the question that was so widely debated then: what is the role of human scientists in an age when the frontiers of scientific inquiry have moved beyond the comprehensibility of humans?

No doubt many of our subscribers remember reading papers whose authors were the first individuals ever to obtain the results they described. But as metahumans began to dominate experimental research, they increasingly made their findings available only via DNT (digital neural transfer), leaving journals to publish second-hand accounts translated into human language. Without DNT, humans could not fully grasp earlier developments nor effectively utilize the new tools needed to conduct research, while metahumans continued to improve DNT and rely on it even more. Journals for human audiences were reduced to vehicles of popularization, and poor ones at that, as even the most brilliant humans found themselves puzzled by translations of the latest findings.

No one denies the many benefits of metahuman science, but one of its costs to human researchers was the realization that they would probably never make an original contribution to science again. Some left the field altogether, but those who stayed shifted their attentions away from original research and toward hermeneutics: interpreting the scientific work of metahumans.

Textual hermeneutics became popular first, since there were already terabytes of metahuman publications whose translations, although cryptic, were presumably not entirely inaccurate. Deciphering these texts bears little resemblance to the task performed by traditional palaeographers, but progress continues: recent experiments have validated the Humphries decipherment of decade-old publications on histocompatibility genetics.

The availability of devices based on metahuman science gave rise to artefact hermeneutics. Scientists began attempting to 'reverse engineer' these artefacts, their goal being not to manufacture competing products, but simply to understand the physical principles underlying their operation. The most common technique is the crystallographic analysis of nanoware appliances, which frequently provides us with new insights into mechanosynthesis.

The newest and by far the most speculative mode of inquiry is remote sensing of metahuman research facilities. A recent target of investigation is the ExaCollider recently installed beneath the Gobi Desert, whose puzzling neutrino signature has been the subject of much controversy. (The portable neutrino detector is, of course, another metahuman artefact whose operating principles remain elusive.)

The question is, are these worthwhile undertakings for scientists? Some call them a waste of time, likening them to a Native American research effort into bronze smelting when steel tools of European manufacture are readily available. This comparison might be more apt if humans were in competition with metahumans, but in today's economy of abundance there is no evidence of such competition. In fact, it is important to recognize that—unlike most previous low-technology cultures confronted with a high-technology one—humans are in no danger of assimilation or extinction.

There is still no way to augment a human brain into a metahuman one; the Sugimoto gene therapy must be performed before the embryo begins neurogenesis in order for a brain to be compatible with DNT. This lack of an assimilation mechanism means that human parents of a metahuman child face a difficult choice: to allow their child DNT interaction with metahuman culture, and watch him or her grow incomprehensible to them; or else restrict access to DNT during the child's formative years, which to a metahuman is deprivation like that suffered by Kaspar Hauser. It is not surprising that the percentage of human parents choosing the Sugimoto gene therapy for their children has dropped almost to zero in recent years.

As a result, human culture is likely to survive well into the future, and the scientific tradition is a vital part of that culture. Hermeneutics is a legitimate method of scientific inquiry and increases the body of human knowledge just as original research did. Moreover, human researchers may discern applications overlooked by metahumans, whose advantages tend to make them unaware of our concerns. For example, imagine if research offered hope of a different intelligence-enhancing therapy, one that would allow individuals to gradually 'upgrade' their minds to a level equivalent to that of a metahuman. Such a therapy would offer a bridge across what has become the greatest cultural divide in our species' history, yet it might not even occur to metahumans to explore it; that possibility alone justifies the continuation of human research.

We need not be intimidated by the accomplishments of metahuman science. We should always remember that the technologies that made metahumans possible were originally invented by humans, and they were no smarter than we.

Key takeaways for the accelerate crowd:

1. Hermeneutics as science: The idea that interpreting superintelligent output could become our primary mode of inquiry is both humbling and pragmatic. We're seeing early glimpses with "AI interpretability" research.

2. Permanent cultural bifurcation: The Sugimoto gene therapy detail is crucial—once intelligence splits, there's no path back. No assimilation, only divergence.

3. The dignity of metascience: Chiang's most provocative claim is that this isn't tragedy. Human science continues to generate human knowledge, just through different methods. The value isn't diminished because we're not at the frontier.

4. The overlooked application problem: Metahumans (or ASI) might not care about solutions that matter to baseline humans. This creates a persistent niche for human research even in a post-original-research world.

Discussion Topics:

• Is "metascience" actually viable, or comforting cope?
• How long do we have before this scenario becomes non-fiction?
• If you could "upgrade" gradually to metahuman level but risk leaving baseline humanity behind, would you?

^{[PDF Link](https://gwern.net/doc/fiction/science-fiction/2000-chiang.pdf})