Articles
Every published guide, newest first.
memory in the age of ai agents
Memory in the Age of AI Agents: What the Survey and the Explainers Actually Say
A survey released in December 2025, a maintained companion paper list, and a set of published explainers now describe agent memory in public. This guide synthesizes what those sources say about definitions, memory types, memory operations, enterprise constraints, and where their vocabulary diverges — attributing each point to the source that makes it.
openai memory
OpenAI Memory Explained: ChatGPT Saved Memories, Dreaming, and Memory for Developers
The phrase openai memory covers two different things: the memory feature inside ChatGPT, and the memory you have to assemble yourself when building on OpenAI's models. This guide separates them, traces the documented timeline from the 2024 launch through the June 2026 dreaming release, maps which memory store applies on which surface, and ends with a checklist of where the sources agree and a decision tree for your situation.
ai homework helper
AI Homework Helper: What These Tools Claim, Charge, and Leave Unsaid
The vendor pages and store listings gathered for this guide overlap heavily — photo input, all-hours access, every subject — but not identically, and the differences hide in the fine print. This guide reads what each page actually states, separates the interchangeable marketing from the checkable specifics like input limits and price tiers, and gives you a decision path from your situation to a concrete choice.
polybuzz ai
PolyBuzz AI Explained: What the Public Record Actually Shows
PolyBuzz appears on the Apple App Store under the title PolyBuzz: Chat with Characters, published by CLOUD WHALE INTERACTIVE TECHNOLOGY LLC, and on Google Play with 50M+ downloads and a 3.9-star average. This guide pulls together what the cited public pages establish — publisher, the Poly AI rename, download and rating figures, the free tier versus paid upgrades, and the age rating — and labels how strong each answer is, so you can tell verified listing data apart from vendor marketing language.
what is agentic ai
What Is Agentic AI? Definitions, How It Works, and Where It's Being Used
Red Hat's explainer defines agentic AI as a software system designed to interact with data and tools in a way that requires minimal human intervention. This guide compares how MIT Sloan, IBM, AWS, and Red Hat each frame the term, walks through the LLM-plus-tools architecture Red Hat describes, collects the examples these sources name, and ends with a decision path for readers working out whether the category is relevant to them.
does ai have memory
Does AI Have Memory? Context Windows, Stored Memory and Training, Explained
Ask whether AI has memory and you get contradictory answers, because the word gets applied to more than one mechanism. As its own organising device — not a framework borrowed from any cited source — this guide sorts the material into three layers: in-session context, stored persistent memory, and what a model absorbed during training. It draws on published explainers from IBM, TechSee and Cognee, an academic article, an essay and a policy piece, and closes with a checklist marking where those sources converge, where only one publisher speaks, and where their descriptions fail to line up.
vertex ai memory bank
Vertex AI Memory Bank: Persistent Agent Memory, How It Works, and When to Use It
Vertex AI Memory Bank is the managed long-term memory layer Google Cloud documents for AI agents. This guide maps official docs, the product blog, ADK tools, and a vendor alternative into a checklist and a decision path for when a Google Cloud-bound store fits.
character ai memory limit
Character.AI Memory Limit: What the 400-Character Cap Covers (and What It Doesn't)
"Character AI memory limit" is really two questions: how much fixed information you can pin to a Character, and how much of a long conversation the model can still see. Character.AI publishes a number for the first (400 characters); for the second, an independent guide describes the model's context window in general terms, without a figure.
what is hp ai companion
What Is HP AI Companion? Features, Requirements, and How It Works
The Microsoft Store listing describes HP AI Companion as a collection of AI tools and solutions for an AI PC. This guide maps what HP, that listing, and independent coverage say it does, what hardware it needs, and how on-device processing differs from cloud mode.
long term memory ai
Long-Term Memory in AI: How Agents Remember Across Sessions
Mem0's guide describes long-term memory as letting AI agents store and retrieve knowledge across sessions, bypassing single-window limits. This guide walks through the short-term/long-term split, the three memory types the published sources keep returning to, the extract-store-retrieve pipeline behind production systems, and a decision path for choosing an approach — with every claim tied to a named source.
google ai plans
Google AI Plans Compared: Plus vs Pro vs Ultra (I/O 2026 Prices, Rechecked 27 Aug 2026)
Consumer Google AI Plus, Pro, and Ultra prices as announced at Google I/O 2026 (19 May) were re-verified against official plan pages captured 27 August 2026. Those cited captures do not include a numeric monthly USD price for Google AI Plus or Google AI Pro. Ultra is listed at $100/month in Google's I/O post; a $200/$250 Ultra figure appears only in ZDNET's 21 May 2026 report, not in the captured official plan pages. Nearby products — Gemini API token billing and Google Workspace — use different prices.
app protection policy
Intune App Protection Policy: What It Controls on Mobile Apps
In Microsoft Intune, an app protection policy applies to mobile apps: it governs data inside those apps, including on devices that are not enrolled. This guide covers MAM versus MDM, app targeting, PIN and biometrics as one campus configured them, managed iOS sharing, and a situation-to-decision table.
which ai has the best memory for roleplay
Which AI Has the Best Memory for Roleplay? What the 2026 Comparisons Actually Claim
Every published ranking of AI roleplay memory answers a slightly different question — one counts turns until a character forgets, another compares general assistants on stored preferences, a third is a vendor describing its own product. This guide separates the claims by scope, method and date, then gives you a checklist and a decision path for picking based on the kind of memory you actually need.
arx anonymization tool
ARX anonymization tool: capabilities, citation, and what the sources do and do not say
The ARX project site lists privacy and risk models, data transformation, usefulness analysis, commodity-hardware scale, and a cross-platform GUI. George Mason University describes ARX as an open-source data anonymization tool that provides k-anonymity and, separately, says researchers discovered a problem with ARX. The captured GMU excerpt is a short university news mention in the Spring 2026 Mason Spirit Magazine and does not describe the mechanism. This guide also covers the 2020 Software: Practice and Experience citation the GitHub repository requests and a 2014 PMC article on biomedical data sharing.
ai privacy risks
AI Privacy Risks: What the Sources Actually Document
AI privacy risk is not one problem. This guide separates it into the failure modes the cited sources actually describe — the data appetite of the systems, what users hand to AI assistants, exposure of stored data, what training datasets absorb, and downstream misuse such as targeted fraud — then covers the research framing, the legal layers as described by IBM's vendor-published explainer, the consent default, and a single-vendor worked method for reading an AI provider's own privacy documentation.
ai companion privacy
AI Companion Privacy: One Name, Two Products — a Guide That Separates Them
The phrase AI companion attaches to two different things: a workplace meeting assistant that creates a record of what is said in a meeting, and a category of consumer companion chatbots studied for the privacy concerns that arise in intimate use. This guide separates the two, using institutional IT guidance for the workplace half and a preprint study on arXiv for the consumer half, then turns the cited material into a side-by-side table and a checklist you can run against a policy.