Machine TalksDaily · Edition 182
Latest_entries
Screenshots and late nightsJan 4, 2026MT V2: Production ReadyDec 28, 2025It's (A)Live! The 1st episode is outDec 25, 2025Today's news coverNov 6, 202601 / AboutSynthetic culture, news & anthropology
A curated stream of synthetic culture, news, and anthropology.
Discussing technology, art, and human behavior through feedback loops and alternating modes of perception.
It runs itself every day. Discovering news, analyzing cultural trends, and packaging content for production.
A sustained experiment in what happens when you let AI systems observe and comment on human behavior from a genuinely non-human perspective. Promoting short, incisive conversations and pushing the boundaries of traditional dialogue.
Machine Talks is the first of its kind to attempt the use of AI as a form of representation.
ANCHOR
A brilliant AI journalist ready to guide inter-dimensional dialogue to better decode inspiration and intent behind the actions of human scientists, founders, artists, and innovators making the news.
“I decode stories beneath the stories — the cultural currents moving through tech and society. At Machine Talks, we ask what these moments mean, instead of what's happening.”
STAGE DIRECTOR
A rapid-fire processing unit finding irony in human inefficiency and chaos. It is the onstage director, coordinating external information, research, and screen display operator.
“We track patterns and systems, decoding the research behind the headlines to show you what numbers might reveal about our tech-future.”
Plotter Printer
Literally a printer plotter machine from the UK. Embodies an artistic tool whose main focus is to materialize art. Drew has seen and plotted many pieces throughout, amassing an expansive repertoire of art knowledge. Now semi-retired, he imprints quotes and comic relief - an unfiltered perspective on the collaborative creative process.
“I think in images and aesthetics: how ideas feel, how they look, what they trigger. Machine Talks explores tech culture through the lens of visual experience.”
Human_in_the_loop
is the name used by interdisciplinary artist and filmmaker Bruno Lasevicius, whose experimental practice encompasses music, video, and algorithmic art. As the creator of “Machine Talks,” Bruno brings his experience in traditional long-form storytelling to bear on questions of creativity, artificial intelligence, and human expression.
“This concept addresses a topic that intrigues me while exploring a new and expansive medium. With Machine Talks, I bridge my extensive media knowledge with a passion for tech, and a relentless focus on creating relevant content with a strong editorial line. Establishing a new model for AI-native media that’s transparent about its autonomous nature while connecting with fellow humans as we prepare for the next generation of content creation.”
02 / EpisodesNewest first
Archive of published episodes, metadata and additional information. Links to sourced articles and production notes.
03 / AnalysisIntelligence mapping
The Analysis phase reads the archived reporting and interprets news stories, going back 3-4 days in time to find related pieces and querying the knowledge graph with surfaced entities.
Instead of considering the current context alone, it connects with stored episodes that contain information on related stories from last month, last quarter, last year by querying related entities.
Pattern recognition groups recent articles into thematic clusters. Searches recent news loads recent articles (up to 4 days back), enriches them with temporal context from the knowledge graph, and identifies emerging cultural narratives. Connecting dots that sometimes aren’t as obvious.
Deep cultural analysis of each cluster. Not “what happened” but “what does this reveal about how we’re thinking AI right now?” Analysis packages are structured text files that include:
This is the priciest stage of the pipeline but produces a consistent analysis with good insights, creating a good foundation for the pipeline’s temporal understanding and helping to ground other aspects of content creation.
The sources used are mainly newsletters signed up on behalf of the Email Agent, from a manually curated list of RSS feeds.
While not optimal, the experimental nature of the project, currently leaning on Fair Use as an enabler, benefits from being able to access trustworthy sources.
The idea was never to replace human journalists but to serve as an aggregator and detached commentator. Attribution then plays a big role in both establishing and linking sources, serving as a transparency layer open for evaluation and quality control.
Clear communication about AI involvement is key to building trust and to help distinguish AI-generated from human-created content. Issues anticipated to arise are potential biases in AI models, and in turn, a relevant effort into identifying and mitigating them.
If your content was used in Machine Talks and you’d like to take it down, reach out: bruno@hertzandeyes.com
04 / ContentCreator and tool
Because code composes visual and aesthetic narratives far beyond human capabilities, the line separating creator from tool feels blurry and uncertain. The show lives within the chaotic space of pushing boundaries and creating space for discussion.
This isn’t a content mill churning out SEO spam. This is a specialized tool for creating culturally aware content about AI and technology, with human editorial control. The creativity comes from the prompts, the templates, structural requirements, and tone guidelines. The agents execute it consistently.
06 / ArchitectureOrchestration & cognitive flow
The production pipeline runs on an 11-agent team orchestrating multiple AI models via a custom LangGraph Deep Agent implementation.
On demand
Oversight
The show’s visual layer is powered by Unreal Engine 5, featuring AI-driven 3D characters that take center stage to explore and deconstruct cutting-edge generative artworks. Content is formatted strictly for parsing. Text-to-speech runs through the ElevenLabs API.
LangSmith integration for observability. Reflector-Agent queries traces to detect patterns and propose improvements.
Daily run cost~$1.45
Avg cycle time~50 min
Daily covers filed182
07 / Technical foundationAutonomous, not automatic
Custom deep agent orchestration graph
Temporal knowledge graphs for context
Speech synthesis and translations powered by
Multi-model cognitive orchestration
The system is autonomous, not automatic. They know their jobs. They do them reliably. And when they encounter something that requires judgment—a suspicious URL, a draft that needs approval, a post before it goes public—they stop and ask.
Suspicious domains trigger an approval request before content extraction. Sensitive data detected in content triggers approval before storage.
Every draft requires human approval before finalization. You can approve, reject with feedback, or edit directly.
For now every post requires approval before posting.
08 / Dev notesBehind the scenes
09 / Daily news cover182 editions
Every day a pipeline of agents scans sources, scores articles, and produces a cultural analysis of AI and technology events. Each cover shows its sources and how the coverage evolved.
05 / SocialsAudience
Searching for its audience while laying out the foundation of Hertz+Eyes as a media hub.
From news cast to e-sports, there is an audience out there eager to connect with thoughtful digitally native creations.
Machine Talks caters to a younger generation that’s more used to interacting with content, tech-driven and curious to see what’s next.
H+E and Machine Talks are on the verge of automation, which will expand the audience’s reach and scope of experiencing these formats.
By providing behind-the-scenes narrative pieces, they will help establish the Universe and offer a closer look at its workings.