A future-facing podcast that explores how augmented reality will show up in our everyday lives, off-screen and all around us. Each episode features everyday people (not tech insiders) grappling with how this new layer of reality could reshape the way we shop, move, learn, or just get through the day. These conversations take abstract ideas and ground them in the practical, turning sci-fi into Saturday morning.
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February 1, 202610 min
[BS] From 2 Weeks to 2 Minutes
I realised recently that the time I was spending sharing my ideas was actually strangling the sharing of ideas themselves. In this BrainStream, I'm opening up about why I'm working to automate my entire production pipeline—from transcripts to clips— to keep sharing. I think we're entering an era where 'janking' together AI tools like Claude Code and Remotion isn't just a hack; it's the only way to keep up with the ROI of our own thoughts. I wonder if the future of the UI isn't just talking to our computers, but having them understand the visual and emotional context of our work before we even ask.Timestamps(0:00) The Guatemala Vision Pro Backlog(2:15) When the ROI of Sharing Doesn't Make Sense(4:10) From 2017 Manual Edits to AI Pipelines(6:20) Automating the 'Boring Stuff': Clips & Captions(8:10) The Post-Siri World: OpenClaw & Agentic FilesystemsListen OnIf you enjoyed this episode, you can listen to more of my brainstreams on Spotify, YouTube, or Apple Podcasts.Check out my website for more insights: https://avrahamrask.in/podcast
January 31, 202610 min
[BS] Why Are You Still a Slave to Your Computer?
We’re finally breaking free from the 1980s desktop paradigm and moving into a world where creation isn’t tied to a workstation. I’m diving into how I finally cracked the code on local automation for the BrainStream, bringing us closer to a future of conversational agents that actually understand and build alongside us. From my early work on the Whisper project to the current shift in spatial computing, we’re exploring how we can stop being tethered to a desk and start leveraging high-fidelity AI collaboration wherever we go.Timestamps[0:00] From GUI to Conversational OS[1:36] The Whisper Vision: Untethered AI[3:12] The High Cost of Manual Friction[4:30] Custom Pipelines Over SaaS Bloat[6:20] Local Video Clipping with Whisper JSON[8:10] Iterative Media & Generative AssetsListen OnIf you enjoyed this episode, you can listen to more of my brainstreams on Spotify, YouTube, or Apple Podcasts.Check out my website for more insights: https://avrahamrask.in/podcast
January 30, 202610 min
[BS] One Year per Day: Scaling Human Insight for the AI Tsunami
The velocity of innovation right now is insane—we’re seeing a year’s worth of progress every week—and the only way to keep up is to automate the friction out of our systems. I’ve finally dialed in a pipeline that handles the heavy lifting of post-production and distribution with a single click, freeing me up to dive deeper into the high-stakes security projects I’ve been teasing. This episode is a direct look at how I’m using AI to reclaim my time, moving away from manual content management and back toward pure insight and execution. If we're going to build the future, we can't afford to be slowed down by the logistics of the present.TIMESTAMPS:0:00 | Navigating the AI Acceleration Curve1:45 | Why Content Friction Stalls Big Ideas3:20 | The Utility of the Spoken Word5:10 | Solving Local vs. Cloud Friction6:55 | Video as Code: The Remotion Shift8:30 | Closing the Agent-Driven LoopLISTEN ONSpotify: https://open.spotify.com/show/0gyQydQ9h5PM2gGUWy1PfCYouTube: https://youtube.com/playlist?list=PLifoYer83q8ACtYWCtjhoOHGmfslydLM7&si=yKhmWU6J9t6j9USFApple Podcasts: https://podcasts.apple.com/us/podcast/id1726877985Website: https://avrahamrask.in/podcast
December 31, 20259 min
[BS] Revisiting the 2025 Concept Series
In this year-end Brainstream, Avraham revisits a 2018–2019 video exploring how augmented reality and AI could transform everyday problem solving. Using the example of fixing a broken fridge, he unpacks multimodal AI—vision, sound, and conversation working together—and reflects on how concepts from seven years ago are becoming increasingly practical today. This episode also considers the evolving relationship between humans and AI in collaborative problem solving.TL;DRA seven-year-old video predicting AI-assisted, AR-driven home repairs highlights how multimodal AI—integrating vision, sound, and conversation—can empower humans to solve problems collaboratively without experts or cloud dependency.🎧 Listen on Spotify | YouTube | Apple PodcastsListen to the full episode and explore more Brainstream → https://avrahamraskin.com/podcast
December 3, 20259 min
[BS] Apple Health, OpenAI, And The Private Missing Piece
A quiet rumour about OpenAI tapping into Apple Health sparks a deeper question: what would a truly private, on-device health intelligence actually look like? Listen on Spotify, YouTube, Apple PodcastsMore episodes → https://avrahamraskin.com/podcastTimestamps00:00 | The Rumour About OpenAI And Apple Health01:06 | Why Access To Raw Health Data Actually Matters01:45 | The Privacy Problem With Cloud-Based LLMs02:26 | The Case For A True On-Device Reasoning Model03:12 | Hardware Limits And Why Models Must Shrink04:26 | What A Smarter Siri Should Really Be05:14 | Health Metrics, Trends, And Real Coaching06:24 | The Missing Link: Nutrition Data07:12 | Rumours Of Apple HealthPlus08:02 | What Real AI Coaching Should Feel Like09:07 | Integrating Sleep, Training, Journaling, And Goals09:48 | The Vision: A Private, Personal, On-Device Coach
November 26, 202510 min
[BS] AI Operators, and the Leap Beyond Alarms
In this BrainStream, I explore why we’re on the edge of a generational shift in how properties are secured. Not just sensors. Not just cameras. A true, always-awake operator built from VLMs, re-identification, and on-prem AI. I look at Ubiquiti’s position, emerging players, and why the “virtual guard” model is no longer sci-fi but an inevitable next step.TL;DRSecurity is moving from alarms to an always-awake, property-aware AI operators that verifies, learns, and predicts.🎧 Listen Now at Spotify, YouTube, or Apple Podcasts→ More at: https://avrahamraskin.com/podcastTimestamps00:00 | Why I Had to Record One More00:21 | The Ubiquiti/UniFi Fascination01:31 | The “Ultimate Operator” Concept02:20 | Parameters → Description: A Real Turning Point03:21 | Teaching an AI the Property (The Guard Analogy)04:41 | From Virtual Guards to Site-Aware Intelligence05:22 | Alarm Monitoring: The Missing Link06:13 | Camera Verification and VLM Reasoning08:48 | Prediction Instead of Reaction09:51 | Closing the Loop: Where This Is Heading#Ubiquiti #UniFi #VideoOperator #VLM #Re-ID #Alarm #Verification #PredictiveSecurity #On-Prem AI #ComputerVision #Security #Future
October 20, 20259 min
[BS] When Cameras Learn: The Rise of Video-Language Models
A concise, investigative tour of how security video evolved from passive cctv to intelligent, searchable footage powered by local ai and video-language models. I maps the technical lineage-motion sensing, smart detections, face and plate id, the “AI Key,” and scene-level vlm search-and explain why pattern discovery at scale is the next operational leap for site security and investigations.“video that used to be passive now becomes a searchable narrative.”🎧 listen on spotify, youtube, apple podcasts🔗 more episodes → https://avrahamraskin.com/podcasttl;drsecurity cameras have graduated from passive recorders to active, searchable sensors. video-language models (vlms) and local llm-like agents enable natural-language scene search and condensed pattern visualisations-powerful for investigations but constrained today by compute and edge deployment. the next frontier is real-time, site-wide pattern detection running at the edge.timestamps00:00 | introduction and context00:23 | the evolution: cctv → motion → smart detections01:56 | face detection, license plates, and granular id02:19 | the “ai key”: local llm-style analytics (what it adds)03:35 | video-language models: frame description → search05:03 | practical investigative tools and scene search examples06:03 | pattern discovery: briefcam and condensed timelines07:40 | limitations today: compute, edge, and the next step09:56 | closing thoughts and what’s next
September 24, 202510 min
[BS] The Future of Security: From Reactive Cameras to Predictive Intelligence
Most security systems still behave like they did 20 years ago-reactive, limited, and blind to the context hidden inside their own recordings. In this Brainstream, we explore why the real frontier in security isn’t better alerts or higher-resolution cameras, but AI systems that can learn a site’s patterns, behaviours, anomalies, and risks over months of recorded footage. This episode outlines the shift from “review after the incident” to “predict before it happens,” and why the intelligence trapped inside our footage is the most valuable, unused asset in modern security.TL;DRSecurity cameras shouldn’t just replay the past-they should understand it. When indexed, analysed, and contextualised, months of footage can power predictive, site-specific intelligence far beyond traditional monitoring.🎧 Listen on Spotify, YouTube, Apple Podcasts🔗 More episodes → https://avrahamraskin.com/podcastTimestamps00:00 | Opening: Why talk about the future of security00:05 | Why this topic needs multiple videos00:08 | A new product direction after years in the field00:19 | The core problem: cameras are reactive00:26 | Footage as an investigative tool, not a live one00:34 | Tools like BriefCam and condensed investigations00:51 | The inevitability of deep pattern analysis01:17 | Rethinking what recorded footage really contains01:26 | On-site storage vs cloud motion clips01:48 | Why modern systems rarely store “everything”02:14 | The hidden value inside long-term footage02:27 | Thought experiment: downloading 6 months of footage into a guard03:06 | Scale: 25–100 cameras, months of data03:25 | What context a human misses vs what the data contains03:58 | Reviewing footage: hours, days, weeks04:25 | Pattern detection after the fact04:54 | The industry’s stuck in reactive mode05:02 | Moving from reactive to predictive05:17 | Connecting dots before the incident05:24 | Trends, anomalies, and site-specific patterns05:34 | What good security guards actually do06:00 | Knowing who belongs and who doesn’t06:13 | Cameras should be able to learn the same06:22 | Context → patterns → prediction06:34 | Generations of camera evolution07:00 | Smart detections: person, car, face, plate07:14 | More granular detection: clothing, colours, models07:36 | Natural-language retrieval: next-generation search07:56 | But still mostly reactive08:03 | True intelligence: learning the site itself08:12 | Threat assessment powered by context08:26 | The massive, untapped value in indexed footage08:51 | Behaviour understanding vs object detection09:04 | AI as a security operator/assistant09:14 | Cameras becoming proactive09:20 | Future episodes: alarms, sensors, monitoring09:33 | Industry progress & uneven advancement09:42 | Why pattern understanding changes everything09:57 | Closing: A new era is coming
August 28, 202514 min
[BS] The Old City Loop: A Light Rail Vision for Jerusalem’s Future
What if you could circle the entire Old City of Jerusalem - comfortably, accessibly, and beautifully? In this episode of Brainstreams, we explore a future-facing vision for a dedicated light rail line that loops around the Old City walls. From smart routing and grade calculations to archaeological sensitivity and pedestrian flow, this Brainstream dives deep into a generative design sprint born from both data and lived experience.TL;DR:A Jerusalem city loop light rail around all seven gates could transform access, beauty, and spiritual flow - this is the design pitch.We discuss multi-line integration (red, brown, yellow), how to preserve archaeology while opening new paths, grading challenges, and why a humble footpath + rail combo might be the most transformative layer Jerusalem’s had in decades.🎧 Listen now on Spotify, YouTube, or Apple Podcasts→ More at avrahamraskin.com/podcastTimestamps:00:00 | Intro: What is the Old City Loop?00:43 | Green space, walking path, and rail: the triple-ring vision01:58 | The gaps in Jerusalem’s current light rail access03:06 | Seven gates, one loop: walking through the plan05:01 | Grades, curvature, and optimal timing06:13 | Integrating with existing and future lines (Red, Yellow, Brown)07:30 | One-way loop + second-direction bus support09:23 | Accessibility at Shaar Tzion & other grading concerns10:00 | Park & Ride potential near Damascus and Dung Gates12:04 | New Gate tradeoffs & archaeological bridge ideas13:06 | Solving steep terrain with design sensitivity14:39 | Closing thoughts: Could this really happen?
July 31, 202514 min
[BS] KoshAR Vision: Could AR Help Revolutionise Grocery Shopping Worldwide?
What if kosher products simply revealed themselves—- guessing, no flipping, no frantic Googling? In this Brainstream, we explore a futuristic vision that’s already partially built: an augmented-reality-based kosher shopping experience. Born from the frustration of finding kosher food in Australia, the idea reimagines the process from the ground up-no lists, no scanning, just visual certainty.TL;DR:Imagine pointing your phone at a supermarket shelf and instantly seeing which products are kosher-powered by AR, crowdsourcing, and smart databases. This Brainstream lays out that vision.We also dive into the pain of local-only kosher databases, the promise of contributor modes, and how we can use computer vision, gamification, and community to create the ultimate global kosher assistant.🎧 Listen now on Spotify, YouTube, or Apple Podcasts→ More at avrahamraskin.com/podcastTimestamps:00:00 — The AR Kosher Shopping Vision00:49 — Growing Up Without Easy Kosher Access02:00 — Kosher Australia App: Helpful But Limited03:04 — The Chocolate Shelf Incident (and UX friction)04:11 — Barcode Scanning: A Step Forward, Still Painful05:25 — Every Country Has Its Own App (if you’re lucky)06:03 — Why Kosher Data Shouldn’t Be Gatekept07:00 — Introducing Contributor Mode & Crowdsourced Verification08:13 — How OCR + Computer Vision Enable Instant Recognition09:23 — Game Mechanics for Certifying Products10:22 — Verification Badges & Authority Endorsements12:01 — The Pay-It-Forward Incentive Loop for Travellers13:03 — Making Kashrut Fun, Seamless, and Fluid14:01 — The Auto-Scan Dream and Proximity-Based Info
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