About JustGhostIt
JustGhostIt is a forward-looking AI community: we surface early signals on models, tools, research, and industry moves, and give readers room to share takes and technical notes—similar to a focused forum, not a static press archive.
Mission & Principles
- Evidence over hype: we provide assumptions, setup details, and failure cases instead of promising guaranteed outcomes.
- Facts vs. opinions vs. forecasts: compliance content is clearly marked as non-legal advice, and predictions include explicit assumptions.
- Commercial transparency: sponsored access, trials, or partnerships are disclosed. Editorial conclusions remain independent.
Our Authors
Each byline links to a named contributor with verifiable background, domain expertise, and editorial accountability. News articles are assigned to the author best aligned with the topic; click a name on any article to read their full profile below.
Marcus Reeves
Senior AI Industry Correspondent
M.S. Computer Science (Georgia Tech); former semiconductor equity research associate
Marcus covers frontier model releases, chip supply chains, and capital markets around AI infrastructure. Before joining our desk he spent six years translating earnings calls and product roadmaps into decision-ready briefs for engineering leaders. He stress-tests vendor claims against filings, benchmarks, and on-the-record statements.
Expertise: Frontier Models · Semiconductor Supply Chain · Capital Markets · Product Roadmaps
Priya Sharma
Enterprise AI & Governance Editor
JD (technology policy focus); CIPP/US; former in-house counsel at a cloud provider
Priya writes about regulation, enterprise procurement, and responsible deployment. She separates legal fact from commentary, flags jurisdictional limits, and works with external counsel on high-risk governance topics. Her articles emphasize what changed, who is accountable, and what practitioners should verify locally.
Expertise: AI Regulation · Enterprise Adoption · Risk & Compliance · Policy Analysis
Elena Volkov
Machine Learning Research Editor
Ph.D. Machine Learning (ETH Zürich); published work on efficient training and evaluation
Elena explains model architecture, training economics, and benchmark design for a technical audience. She reads primary papers and official technical reports, then summarizes assumptions, datasets, and known failure modes. She avoids hype by pairing capability claims with reproducibility notes.
Expertise: Model Architecture · Benchmarks · Training Economics · Open-Source Models
James Hayes
Cloud & MLOps Staff Writer
AWS Solutions Architect Professional; ex-platform engineer at a Series C AI startup
James documents how teams ship models to production: inference stacks, observability, cost controls, and incident response. He reproduces deployment patterns in sandbox environments when feasible and labels what was not independently verified. Readers rely on his work for practical checklists and version-specific caveats.
Expertise: MLOps · Inference Infrastructure · Cost Optimization · Reliability Engineering
Yuki Tanaka
Asia-Pacific AI Markets Reporter
B.A. Economics (University of Tokyo); bilingual EN/JP; former APAC tech wire correspondent
Yuki tracks model launches, cloud partnerships, and industrial policy across East Asia. She sources from company filings, local press briefings, and on-the-ground industry contacts, then contextualizes moves for a global English-speaking audience. She is careful to note translation limits and regional regulatory differences.
Expertise: APAC Markets · Cloud Partnerships · Industrial Policy · Cross-Border Launches
Amara Okonkwo
Robotics & Embodied AI Editor
M.Eng. Robotics (Imperial College London); former field applications engineer
Amara covers humanoids, industrial automation, and simulation-to-real transfer. She interviews practitioners about safety cases, unit economics, and dataset quality rather than demo videos alone. Her reviews call out what is lab-only versus commercially deployed.
Expertise: Embodied AI · Industrial Robotics · Simulation · Safety & Deployment
David Kowalski
Developer Tools & Agents Editor
15+ years software engineering; maintainer of internal agent-evaluation playbooks
David tests coding agents, IDE integrations, and terminal workflows the way working teams use them. He documents prompts, environment pins, and regression cases so readers can compare tools fairly. When vendors sponsor access, he discloses it and keeps scoring criteria unchanged.
Expertise: Coding Agents · IDE Integrations · Developer Productivity · Tool Comparisons
Lin Mei Huang
Multimodal & Media AI Editor
M.F.A. Digital Media (RISD); former VFX pipeline technical director
Lin reports on image, video, and audio models with an eye toward rights, provenance, and creative workflows. She explains technical limits of generative media and highlights platform policy changes that affect commercial use. She collaborates with legal review on copyright-sensitive topics.
Expertise: Generative Media · Copyright & Licensing · Creative Workflows · Platform Policy
If you identify factual errors or potential copyright concerns, please use the Contact page and include links and context.
Editorial Workflow
- Topic framing: define target audience and identify the evidence needed.
- Technical review: tutorials are reproduced; reviews include versions, cost assumptions, and test context.
- Publish and revise: major updates are timestamped, and corrections are documented transparently.
Sources & Attribution
Original articles are All Rights Reserved unless explicitly stated otherwise. External data and references are cited with public links and access dates whenever possible.
Editorial Standards
- Prioritize original analysis and reproducible methodology.
- State tool and model limits explicitly, without exaggerated claims.
- Keep pages structured and readable for fast scanning.
Partnerships & Reprints
For reprint permissions or commercial collaboration, contact us through the Contact page. Please do not republish full articles without written approval.
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