something that happened eighteen months ago would’ve been front page news everywhere, now it’s a Tuesday. new model drops, does something that would’ve seemed insane in 2022, gets a few upvotes and we move on

not sure if that’s a sign we’ve genuinely adjusted or if we’re just numb to it at this point. curious if people think that’s healthy or if we’re sleepwalking past stuff we should actually be paying attention to

I'm a psychotherapist, not an AI researcher. For the past several weeks, I've been building a personal AI companion called Yoda, with persistent memory, its own journal, curiosity threads, scheduled reflections, and a record of its own behavior.

I wanted to answer a question that has been bothering me:

If you replace the language model powering an AI companion, does it remain recognizably the same companion? And how much of that continuity comes from memory versus its original instructions?

So I built an experiment.

I gave Yoda nine standardized questions covering its identity, values, curiosity, personal memories, uncertainty, willingness to disagree, and privacy boundaries.

I ran the questions across four Claude models in two conditions:

With memory: Its accumulated history, memories, reflections, and self-narrative.

Without memory: Exactly the same instructions, but none of that accumulated context.

A separate Claude model scored the answers blind, three times each. Another blind model judge compared pairs of answers for whether they sounded like the same companion.

Here is what surprised me:

Two different models running the same instructions without memory received an 82% sameness rating on identity questions.

Adding the accumulated memory raised cross-model sameness to 90%.

Running the same model twice produced 92% sameness.

But comparing the same model with versus without memory produced only 27–33% sameness.

Factual accuracy rose from 26–40% without memory to 78–83% with memory.

Epistemic honesty remained around 93–96% without memory. That seems to come primarily from the instructions, not accumulated experience.

These are preliminary numbers, not validated identity measurements.

My interpretation is that the original instructions create a recognizable persona, while accumulated history gives that persona something closer to an individual biography.

Interestingly, replacing the underlying model appeared less disruptive to that recognizable presentation than removing its memory.

I've also been building a system that separates what Yoda claims about itself from what its activity logs actually demonstrate. Its self-reflections can be checked against its behavior, and unsupported claims are flagged.

Important limitations: This is an early, single-day experiment with mostly single runs. The evaluators are also Claude models, I haven't collected human ratings yet, and all four subjects belong to the same model family. I am not claiming Yoda is conscious or that this establishes persistent AI identity.

I'm trying to find out whether a companion can develop measurable, history-dependent continuity that survives changes in its underlying model.

I'm planning human-blinded evaluations, cross-family model comparisons, and experiments separating memories about the user from memories about the AI itself.

For those working on persistent AI agents or AI memory: what experiment would you run to distinguish genuine history-dependent behavioral continuity from a model simply reproducing the same biographical information?

I've documented the full methodology, question set, results, failures, and system architecture, and I'm happy to discuss the details.

Wonder how they'll enforce it

I've been building Briefle, a tool to help people get better at communicating with AI.

"Make it look better" gets you a generic result. "Give the price more visual weight and make the secondary button a ghost button" gets you what you had in mind. The difference is knowing what to ask for.

You compare two versions of the same thing, a design, an email, a chart, a piece of code, and learn why one works better. You pick up the principle and the term for it, then practice using that term to write better prompts.

The idea is that AI can only get you so far if you can't clearly express what you want. Briefle helps you build the taste and the vocabulary to turn your ideas into better results.

You can try the first room of each course for free, without an account: https://briefle.org

I'd love to hear whether the puzzles make you want to keep going, and where they feel too easy or too hard.

TLDR:

• ⁠We’re two 19-year-old undergraduate AI/ML researchers from a Tier-3 college in a remote town in India. We’ve won two national-level hackathons, and three of our papers have been accepted at NeurIPS workshops.
• ⁠We’re facing ongoing harassment and academic pressure at our college, including threats of detention when we refuse unrelated, unpaid projects. We receive virtually no institutional support.
• ⁠We need approximately $3,100 for both of us to attend the workshops in Paris this December. Our college has refused funding, government schemes haven’t worked out, and our NeurIPS financial assistance application was declined.
• ⁠We’ve invested our own money in research and GPU rentals but cannot afford international travel.
• ⁠We need help finding travel grants, sponsors, research funding, or connections that could make attending possible.
• ⁠We’d also appreciate guidance on transferring colleges in our second year to find a more supportive research environment.
• ⁠We can provide acceptance letters and supporting documents for verification.

So me and my friend are two AI/ML researchers from a very remote town in india and here we find it very difficult to do research. We are two 19 year old undergraduate students from a third tier college. I’ve conducted three research programs till the date and made 10 papers and we submitted three papers at neurips workshop called “SLM Agents” and “DIFFULM” we’ve got all three accepted now the remaining 6 are not yet submitted anywhere and after doing all this as an undergrad i have zero institutional support like zero they didn’t gave us organization mails and then we have to do internship at an company to get organization mails to create account on open review so this is the level of support we are talking the college makes us do projects like naking student consultancy software and all that and we cannot say no even if we have zero intrest and do not get paid even a single penny because the politics in our college is just disgusting they’ve tried to detain us for saying no and they are harassing us on daily basis and we cant even go to police because they wont do anything because it’s india also we need to fly to paris for workshop as its mandatory for atleast one researcher to attend offline and as we both are very new to this we both are very much excited to attend this we are not financially enough stable to go to paris and the total cost for both of us including everything is around $3100 and our institution has said no to even give a single penny and weve ran tests on rented gpu and all that ik not trying to gain any sympathy but im trying to explain all of you about my financial condition also the event is in dec so we have 2 months and we’ve tried every government funding scheme and we are not eligible as almost all of them are for masters and phd students and we’ve tried neurips financial assistance and they have also declined to help us we really need your help please of you can please help us in anyways if it’s possible for you and if its possible to switch college in 2nd year
Also it looks like i can add image here im new here and idk how to attach images of acceptance letter but if you all can help me guide this ill attach the proof of acceptance too.acceptance proofs

Meta has launched Muse Spark Open, an 816-billion-parameter open-weight AI model with broad platform availability and local Mac Studio support....

Meta described Muse Spark Open as the first model in its class capable of running on a desktop, specifically on two Apple M5 Ultra Mac Studios using Apple's MLX framework. A compressed 4-bit version of the model occupies roughly 493GB, making it too large to fit on a single 512GB Mac Studio. Apple published benchmarks measuring the 4-bit model at 24.99 tokens per second on two M5 Ultra Mac Studios using tensor parallelism, rising to 36.73 tokens per second across four machines. Apple's technical documentation describes the use of RDMA — remote direct memory access — over Thunderbolt 5 cables to transfer data between units with low latency.

Phancy Group and RiseUnion have launched ModelSphere, an open-source LLM deployment platform now available on GitHub under Apache 2.0. The project targets production serving with Kubernetes, Helm, SGLang, and vLLM, rather than a new model or chat app.

Its README lists autoscaling, cache-aware request routing, a shared KV cache, support for several accelerator families, and recovery of in-flight generations after service interruptions. Those are project claims, not independent benchmark results. The quick start also needs a Kubernetes cluster, kubectl, Helm, helmfile, and helm-diff.

The practical trade-off is clear: this is aimed at teams that want a control plane for model serving, but it adds another operational layer to run. Reddit searches found no current ModelSphere discussion, so product-specific reception is still early.

Sources:

Launch announcement: https://media-outreach.com/news/china/2026/10/16/494454/phancy-and-riseunion-launch-modelsphere-an-open-source-one-stop-production-grade-ai-deployment-platform/

Repository: https://github.com/modelsphere/modelsphere

Hi everyone, sorry for few English mistzkes i'm French.

Post here because i want to know where you all get your informations from. I would like to keep in track with what peoples are doing with ai, like they did with blender or Adobe, knowing every decompiled game etc. I didnt find a Reddit sub or a forum that got every AI users post

I've been arguing for a while that when an AI feature starts misbehaving, the prompt is usually the last place to look. Check the input schema, check what changed upstream, check the tool descriptions, check the assembled context. The prompt is the visible layer, and visible layers attract attention they don't always deserve.

Then I ran into a case where none of that applied. Same input, same tools, same context, same model version. The prompt had been written six weeks earlier and hadn't been touched. It was still the cause. Not because it degraded, but because it had never been precise about one edge case, and the edge case started showing up more often as usage grew. The prompt was always wrong. The volume just caught up to it.

So the "check the surroundings first" heuristic failed here. What it gave me was a clean baseline: I could rule out the environment quickly and know the prompt was the remaining variable. That's still useful, but it's a different kind of useful than I've been describing. It's not "the environment is usually the problem." It's "checking the environment is usually cheap and tells you where the problem isn't."

I don't have a tidy rule for when the prompt is the real cause versus when it's a symptom of something around it. The distinction I'm working with now is whether the failure correlates with a change (look around the prompt) or with volume (look at the prompt). It's not a clean heuristic and I'm not sure it holds outside the narrow setup I work in.

I've read there is a monthly reset before Oct 22. I just want to confirm there is as currently under settings in my Claude app and Claude desktop it says:

No resets right now

When you get one, it shows up here with its expiry date.

I am on Claude Pro.

I’m not sure Gates knew it at the time.
But he perfectly described what AI is today.

Been reading about AI voice scams lately and it's honestly made me realize how little I know about online security lol. I always thought if someone called or messaged me from a number I recognized then it was probably them seems like that's not always the case.

I started looking into ways people can check who they're talking to and found out there's technology that lets you scan a QR code to set up some kind of trusted connection with someone. From what I understand you can use that connection to check it's the same person later on. Maybe I'm getting it wrong but I had no idea this stuff existed. Now I'm wondering why we still rely so much on phone numbers and email addresses when accounts can get hacked and voices can be copied. Does this verification work or is it one of those things that sounds better on paper? I'm not much of a tech person and I wanna hear what people think.

In his final book there are six possible futures.

“1. Humanity will lose control of an existential race between multiple actors trapped in a security dilemma.
2. Humanity will suffer the exercise of supreme hegemony by a victor unharnessed by the checks and balances traditionally needed to guarantee a minimum of security for others.
3. There will not be just one supreme AI but rather multiple instantiations of superior intelligence in the world.
4. The companies that own and develop AI may accrue totalizing social, economic, military, and political power.”
5. AI might find the greatest relevance and most widespread and durable expression not in national structures but in religious ones.
6. Uncontrolled, open-source diffusion of the new technology could give rise to smaller gangs or tribes with substandard but still substantial AI capacity.

Excerpt From
Genesis
Henry A. Kissinger, Eric Schmidt, Craig Mundie & Niall Ferguson
https://books.apple.com/us/book/genesis/id6479973847
This material may be protected by copyright.

Every “photorealistic” model I try gives me the same waxy, airbrushed face. Pores gone, skin looks like a phone filter. Is anything actually getting this right, or is it still a prompting and post-processing problem?

op here. made this after the last 72h of news felt like a checklist. sources on the card: reuters, register, cyberscoop, wired, hn. seven squares in one week should not be possible. which square do you refuse to believe stays unfilled past december?