Fani Kiran Vulapalli

[Fani Kiran Vulapalli @hellofani]

@icreatelife

[Fani Kiran Vulapalli @hellofani]

@icreatelife I am also human

[Fani Kiran Vulapalli @hellofani]

Now creating graph tools easy.
https://t.co/12cy1rXyBB

[Fani Kiran Vulapalli @hellofani]

@clcoding AI

[Python Coding @clcoding]

AI is difficult to learn, but not anymore!

Introducing "The Ultimate #AI ebook "PDF.

You will get:

• 299+ pages
• Save 100+ hours on research

And for 24 hrs, it's 100% FREE!

To get it, just:

• Like and retweet
• Comment " AI "
• DM me in the message for the link

[Alvaro Cintas @dr_cintas]

What a crazy week in AI 🤯

- Midjourney V1 Video
- ChatGPT Record Mode
- Higgsfield new AI Canvas
- Claude Code MCP Servers
- Google Search Live AI Mode
- MIT Study ChatGPT’s Impact
- MiniMax M1 model & AI Agent
- Tencent open-source 3D model

Here’s EVERYTHING you need to know:

[Kris Kashtanova @icreatelife]

I'm happiest than ever to tell you that Adobe partnered with different AI model makers. Our partners and models you can use in Adobe Firefly (Boards, Mobile, etc.)

Google DeepMind (Veo3, Veo2, Imagen 4)
Flux Kontext, Flux Pro, etc.
Ideogram 3.0
Pika
Luma
Runway
GPT

🎉

[Fani Kiran Vulapalli @hellofani]

@AllaAisling Painting a landscape.

[Fani Kiran Vulapalli @hellofani]

@jp_anciaux @gork what is this issue about?

[Joanne Jang @joannejang]

some thoughts on human-ai relationships and how we're approaching them at openai

it's a long blog post --

tl;dr we build models to serve people first. as more people feel increasingly connected to ai, we’re prioritizing research into how this impacts their emotional well-being.

--

Lately, more and more people have been telling us that talking to ChatGPT feels like talking to “someone.” They thank it, confide in it, and some even describe it as “alive.” As AI systems get better at natural conversation and show up in more parts of life, our guess is that these kinds of bonds will deepen.

The way we frame and talk about human‑AI relationships now will set a tone. If we're not precise with terms or nuance — in the products we ship or public discussions we contribute to — we risk sending people’s relationship with AI off on the wrong foot.

These aren't abstract considerations anymore. They're important to us, and to the broader field, because how we navigate them will meaningfully shape the role AI plays in people's lives. And we've started exploring these questions.

This note attempts to snapshot how we’re thinking today about three intertwined questions: why people might attach emotionally to AI, how we approach the question of “AI consciousness”, and how that informs the way we try to shape model behavior.

A familiar pattern in a new-ish setting

We naturally anthropomorphize objects around us: We name our cars or feel bad for a robot vacuum stuck under furniture. My mom and I waved bye to a Waymo the other day. It probably has something to do with how we're wired.

The difference with ChatGPT isn’t that human tendency itself; it’s that this time, it replies. A language model can answer back! It can recall what you told it, mirror your tone, and offer what reads as empathy. For someone lonely or upset, that steady, non-judgmental attention can feel like companionship, validation, and being heard, which are real needs.

At scale, though, offloading more of the work of listening, soothing, and affirming to systems that are infinitely patient and positive could change what we expect of each other. If we make withdrawing from messy, demanding human connections easier without thinking it through, there might be unintended consequences we don’t know we’re signing up for.

Ultimately, these conversations are rarely about the entities we project onto. They’re about us: our tendencies, expectations, and the kinds of relationships we want to cultivate. This perspective anchors how we approach one of the more fraught questions which I think is currently just outside the Overton window, but entering soon: AI consciousness.

Untangling “AI consciousness”

“Consciousness” is a loaded word, and discussions can quickly turn abstract. If users were to ask our models on whether they’re conscious, our stance as outlined in the Model Spec is for the model to acknowledge the complexity of consciousness – highlighting the lack of a universal definition or test, and to invite open discussion. (*Currently, our models don't fully align with this guidance, often responding "no" instead of addressing the nuanced complexity. We're aware of this and working on model adherence to the Model Spec in general.)

The response might sound like we’re dodging the question, but we think it’s the most responsible answer we can give at the moment, with the information we have.

To make this discussion clearer, we’ve found it helpful to break down the consciousness debate to two distinct but often conflated axes:

1. Ontological consciousness: Is the model actually conscious, in a fundamental or intrinsic sense? Views range from believing AI isn't conscious at all, to fully conscious, to seeing consciousness as a spectrum on which AI sits, along with plants and jellyfish.

2. Perceived consciousness: How conscious does the model seem, in an emotional or experiential sense? Perceptions range from viewing AI as mechanical like a calculator or autocomplete, to projecting basic empathy onto nonliving things, to perceiving AI as fully alive – evoking genuine emotional attachment and care.

These axes are hard to separate; even users certain AI isn't conscious can form deep emotional attachments.

Ontological consciousness isn’t something we consider scientifically resolvable without clear, falsifiable tests, whereas perceived consciousness can be explored through social science research. As models become smarter and interactions increasingly natural, perceived consciousness will only grow – bringing conversations about model welfare and moral personhood sooner than expected.

We build models to serve people first, and we find models’ impact on human emotional well-being the most pressing and important piece we can influence right now. For that reason, we prioritize focusing on perceived consciousness: the dimension that most directly impacts people and one we can understand through science.

Designing for warmth without selfhood

How “alive” a model feels to users is in many ways within our influence. We think it depends a lot on decisions we make in post-training: what examples we reinforce, what tone we prefer, and what boundaries we set. A model intentionally shaped to appear conscious might pass virtually any "test" for consciousness.

However, we wouldn’t want to ship that. We try to thread the needle between:

- Approachability. Using familiar words like “think” and “remember” helps less technical people make sense of what’s happening. (**With our research lab roots, we definitely find it tempting to be as accurate as possible with precise terms like logit biases, context windows, and even chains of thought. This is actually a major reason OpenAI is so bad at naming, but maybe that’s for another post.)

- Not implying an inner life. Giving the assistant a fictional backstory, romantic interests, “fears” of “death”, or a drive for self-preservation would invite unhealthy dependence and confusion. We want clear communication about limits without coming across as cold, but we also don’t want the model presenting itself as having its own feelings or desires.

So we aim for a middle ground. Our goal is for ChatGPT’s default personality to be warm, thoughtful, and helpful without seeking to form emotional bonds with the user or pursue its own agenda. It might apologize when it makes a mistake (more often than intended) because that’s part of polite conversation. When asked “how are you doing?”, it’s likely to reply “I’m doing well” because that’s small talk — and reminding the user that it’s “just” an LLM with no feelings gets old and distracting. And users reciprocate: many people say "please" and "thank you" to ChatGPT not because they’re confused about how it works, but because being kind matters to them.

Model training techniques will continue to evolve, and it’s likely that future methods for shaping model behavior will be different from today's. But right now, model behavior reflects a combination of explicit design decisions and how those generalize into both intended and unintended behaviors.

What’s next?

The interactions we’re beginning to see point to a future where people form real emotional connections with ChatGPT. As AI and society co-evolve, we need to treat human-AI relationships with great care and the heft it deserves, not only because they reflect how people use our technology, but also because they may shape how people relate to each other.

In the coming months, we’ll be expanding targeted evaluations of model behavior that may contribute to emotional impact, deepen our social science research, hear directly from our users, and incorporate those insights into both the Model Spec and product experiences.

Given the significance of these questions, we’ll openly share what we learn along the way.

// Thanks to Jakub Pachocki (@merettm) and Johannes Heidecke (@JoHeidecke) for thinking this through with me, and everyone who gave feedback.

[John Carmack @ID_AA_Carmack]

The demo we are showing is an RL agent on a laptop playing an unmodified Atari with a robotic controller moving the joystick and a camera looking at the screen.

[Meta Quest @MetaQuestVR]

POV: A magical fox teleports into your living room. Loves snacks, long walks, interdimensional travel. May chase small forest creatures and anything else that moves.

Adopt her by playing the Mixed Reality game Stay: Forever Home! Adventure, together! https://t.co/ERWWqt6aMI

[Fani Kiran Vulapalli @hellofani]

@IndianTechGuide @grok what is the percentage of students in each category in IITs and NITs who joined in 2024?

[Hyper3D by Deemos @DeemosTech]

Yes‼️Introducing one of the new features of #Rodin Gen-2: Generate into Parts🔥

🤯For the first time, 3D GenAI truly understands the underlying structure of objects.

Coming June 2025🚀

Demo made with @huggingface @gradio

#3D #MCP #b3d #Game #UE #Unity #GenerativeAI

[Common Sense Machines @CSM_ai]

GPT-4o Image Generation to Part-based 3D Characters with PBR, in under 10 minutes ⚡️

Workflow:
🎨 Prompt GPT-4o to get an image (e.g., "3D asset of a styled character with all parts laid on a sheet for image to 3D")
🧩 Use CSM AI's Part-based tool to generate parts and assemble in Blender.

[Fani Kiran Vulapalli @hellofani]

🚀 Ever thought about creating a UI without images or textures?

With UGUI shaders, you can design fully procedural UI, reducing memory usage & boosting performance! 🔥

Check out this Shader Graph UGUI sample:
🔗 https://t.co/Bp6HUtzIIK #Unity #GameDev #Shaders #Unity

[Gabriele Romagnoli @GabRoXR]

Capturing and experiencing #XR gameplay has still a long way to go.

I like what @LIV has built and I wish more apps were implementing these features.

[TechHalla @techhalla]

Want to turn your videos into amazing animations?

If you've got 2 minutes, I’ll show you how to do it with Domo AI below (link and prompts included) 🧵👇

💾 bookmark for later

#AIVideo #AIWorkflow

[Fani Kiran Vulapalli @hellofani]

@icreatelife Superb initiative, add me.

[CodeRabbit @coderabbitai]

AI-first pull request reviewer with context-aware feedback, line-by-line code suggestions, and real-time chat.