Canberra AI: Unclassified

There is too much noise out there. Headlines are screaming about the apocalypse, vendors are promising magic, and meanwhile, we’re all just trying to figure out what this actually means for our life, our work, and our future.
​Let’s get back to basics.
​We believe the best way to learn isn’t through a lecture, but through community. We learn faster when we learn together, asking the questions that actually matter without fear of judgment.
​We’ve done the heavy lifting so you don’t have to. We have spent the last decade deep in the trenches of AI research—writing the code, publishing the papers, and reading the dense academic journals—so we can distill it down into plain English for you. We filter the signal from the noise.
​This is an "Ask Us Anything" session. No script. No sales pitch. Just honest answers.
​Bring your question and skepticism. Backed up by scientific research, we’ll be discussing questions like:

• ​"Is AI actually smarter than a PhD, or is it just a really confident parrot?"
• "When we say AI can 'see' or 'hear,' what is it actually doing?"
• ​"If I put a policy draft into ChatGPT, who owns it? Does it keep my secrets?"
• ​"Is 'Prompt Engineering' a real skill, or just a buzzword?"
• ​"Are we at the age of AGI (Artificial General Intelligence) yet, or is that just sci-fi?"

​Whether you’re an expert or you’ve never used a chatbot in your life, you belong here. This is a space to clear the fog and build a shared understanding.

In November last year, we showed you how to build rapid AI prototypes. The room was so packed and the questions so intense, we literally ran out of time.
​But knowing how to build is only 10% of the battle. The other 90% is navigating the "Department of No"—the legal hurdles, the risk-averse executives, and the cultural fear that kills innovation before it ships.
​We are back for Part II.
​Harshil Siyani returns to sit down with Cheng Yu (Trellis Data) for the conversation we didn't get to finish. We are moving from the "Code" to the "Culture."
​
​Big thanks:
​To Trellis Data, ACS Canberra Branch for sponsoring this event.

Recent advances in foundation models are reshaping how we understand perception across vision, audio, and language. Following the success of Segment Anything in computer vision (SAM 1, 2, 3), Meta’s SAM Audio (SAM A) extends the idea of promptable segmentation into the audio domain, enabling open-ended sound separation driven by text, visual cues, or temporal spans.

This research-focused meetup introduces SAM Audio and situates it within the broader trajectory of Perception Encoder, Meta’s NeurIPS Oral work on unified multimodal perception. Rather than viewing SAM Audio as a standalone system, we explore how promptability, audio–visual grounding, and general-purpose perception encoders come together to support flexible, interactive audio segmentation.

We will discuss the design motivations behind SAM Audio, the role of Perception Encoder / PE-AV as a shared multimodal backbone, and how prior work in audio–visual learning, contrastive audio–language alignment, and generative modeling influenced its architecture.

Related Resources:
- SAM Audio Blog: https://ai.meta.com/blog/sam-audio/
- SAM Audio demo: https://ai.meta.com/samaudio/
- SAM Audio paper: https://ai.meta.com/research/publications/sam-audio-segment-anything-in-audio/
- Perception Encoder paper: https://arxiv.org/abs/2504.13181