We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies. .
Cookie settingsACCEPT
NecessaryAlways Active
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
- Cookie
__cf_bm
- Duration
1 hour
- Description
This cookie, set by Cloudflare, is used to support Cloudflare Bot Management.
- Cookie
_pxvid
- Duration
1 year
- Description
PerimeterX sets this cookie to detect fraud and bot activity.
- Cookie
_px3
- Duration
6 minutes
- Description
This cookie is set by the Bloomberg to protect the site from BOT attacks.
- Cookie
CookieLawInfoConsent
- Duration
1 year
- Description
CookieYes sets this cookie to record the default button state of the corresponding category and the status of CCPA. It works only in coordination with the primary cookie.
- Cookie
cookielawinfo-checkbox-necessary
- Duration
11 months
- Description
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
- Cookie
cookielawinfo-checkbox-others
- Duration
1 year
- Description
Set by the GDPR Cookie Consent plugin, this cookie stores user consent for cookies in the category "Others".
- Cookie
cookielawinfo-checkbox-non-necessary
- Duration
11 months
- Description
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Non Necessary".
- Cookie
cookielawinfo-checkbox-analytics
- Duration
1 year
- Description
Set by the GDPR Cookie Consent plugin, this cookie records the user consent for the cookies in the "Analytics" category.
- Cookie
cookielawinfo-checkbox-performance
- Duration
1 year
- Description
Set by the GDPR Cookie Consent plugin, this cookie stores the user consent for cookies in the category "Performance".
- Cookie
cookielawinfo-checkbox-uncategorized
- Duration
1 year
- Description
The cookie is set by the GDPR Cookie Consent plugin to record the user consent for cookies in the category "Uncategorized".
- Cookie
cookielawinfo-checkbox-functional
- Duration
1 year
- Description
The GDPR Cookie Consent plugin sets the cookie to record the user consent for the cookies in the category "Functional".
- Cookie
cookielawinfo-checkbox-advertisement
- Duration
1 year
- Description
Set by the GDPR Cookie Consent plugin, this cookie records the user consent for the cookies in the "Advertisement" category.
- Cookie
wpEmojiSettingsSupports
- Duration
session
- Description
WordPress sets this cookie when a user interacts with emojis on a WordPress site. It helps determine if the user's browser can display emojis properly.
- Cookie
VISITOR_PRIVACY_METADATA
- Duration
6 months
- Description
YouTube sets this cookie to store the user's cookie consent state for the current domain.
- Cookie
viewed_cookie_policy
- Duration
11 months
- Description
The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
- Cookie
PHPSESSID
Duration
Description
This cookie is native to PHP applications. The cookie is used to store and identify a users' unique session ID for the purpose of managing user session on the website. The cookie is a session cookies and is deleted when all the browser windows are closed.
- Cookie
__cfduid
- Duration
4 weeks
- Description
The cookie is set by CloudFare. The cookie is used to identify individual clients behind a shared IP address d apply security settings on a per-client basis. It doesnot correspond to any user ID in the web application and does not store any personally identifiable information.
Functional
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
- Cookie
yt-remote-connected-devices
- Duration
never
- Description
YouTube sets this cookie to store the user's video preferences using embedded YouTube videos.
- Cookie
ytidb::LAST_RESULT_ENTRY_KEY
- Duration
never
- Description
The cookie ytidb::LAST_RESULT_ENTRY_KEY is used by YouTube to store the last search result entry that was clicked by the user. This information is used to improve the user experience by providing more relevant search results in the future.
- Cookie
yt-remote-device-id
- Duration
never
- Description
YouTube sets this cookie to store the user's video preferences using embedded YouTube videos.
- Cookie
yt-remote-session-name
- Duration
session
- Description
The yt-remote-session-name cookie is used by YouTube to store the user's video player preferences using embedded YouTube video.
- Cookie
yt-remote-fast-check-period
- Duration
session
- Description
The yt-remote-fast-check-period cookie is used by YouTube to store the user's video player preferences for embedded YouTube videos.
- Cookie
yt-remote-session-app
- Duration
session
- Description
The yt-remote-session-app cookie is used by YouTube to store user preferences and information about the interface of the embedded YouTube video player.
- Cookie
yt-remote-cast-available
- Duration
session
- Description
The yt-remote-cast-available cookie is used to store the user's preferences regarding whether casting is available on their YouTube video player.
- Cookie
yt-remote-cast-installed
- Duration
session
- Description
The yt-remote-cast-installed cookie is used to store the user's video player preferences using embedded YouTube video.
- Cookie
na_id
- Duration
1 year
- Description
This cookie is set by Addthis.com to enable sharing of links on social media platforms like Facebook and Twitter
- Cookie
vc
- Duration
1 year
- Description
This cookie is set by addthis.com on sites that allow sharing on social media.
- Cookie
__atuvc
- Duration
1 year
- Description
This cookie is set by Addthis to make sure you see the updated count if you share a page and return to it before our share count cache is updated.
- Cookie
__atuvs
- Duration
30 minutes
- Description
This cookie is set by Addthis to make sure you see the updated count if you share a page and return to it before our share count cache is updated.
- Cookie
ouid
- Duration
1 year
- Description
The cookie is set by Addthis which enables the content of the website to be shared across different networking and social sharing websites.
Analytics
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
- Cookie
_ga_*
- Duration
1 year 1 month 4 days
- Description
Google Analytics sets this cookie to store and count page views.
- Cookie
_ga
- Duration
2 years
- Description
This cookie is installed by Google Analytics. The cookie is used to calculate visitor, session, camapign data and keep track of site usage for the site's analytics report. The cookies store information anonymously and assigns a randoly generated number to identify unique visitors.
- Cookie
sbjs_migrations
- Duration
session
- Description
Sourcebuster sets this cookie to identify the source of a visit and stores user action information in cookies. This analytical and behavioural cookie is used to enhance the visitor experience on the website.
- Cookie
sbjs_current_add
- Duration
session
Description
Cookie
sbjs_first_add
- Duration
session
Description
Cookie
sbjs_current
- Duration
session
Description
Cookie
sbjs_first
- Duration
session
Description
Cookie
sbjs_udata
- Duration
session
Description
Cookie
sbjs_session
- Duration
1 hour
Description
Cookie
tk_or
- Duration
1 year 1 month 4 days
- Description
JetPack plugin sets this referral cookie on sites using WooCommerce, which analyzes referrer behaviour for Jetpack.
- Cookie
tk_r3d
- Duration
3 days
- Description
JetPack installs this cookie to collect internal metrics for user activity and improve user experience.
- Cookie
tk_lr
- Duration
1 year
- Description
JetPack plugin sets this referral cookie on sites using WooCommerce, which analyzes referrer behaviour for Jetpack.
- Cookie
tk_ai
- Duration
1 year
- Description
JetPack sets this cookie to store a randomly-generated anonymous ID used only within the admin area and for general analytics tracking.
- Cookie
tk_tc
- Duration
session
- Description
JetPack sets this cookie to record details on how users use the website.
- Cookie
_gat_gtag_UA_5784146_31
- Duration
1 minute
- Description
Google Used to distinguish users.
- Cookie
GPS
- Duration
30 minutes
- Description
This cookie is set by Youtube and registers a unique ID for tracking users based on their geographical location
- Cookie
__gads
- Duration
2 years
- Description
This cookie is set by Google and stored under the name dounleclick.com. This cookie is used to track how many times users see a particular advert which helps in measuring the success of the campaign and calculate the revenue generated by the campaign. These cookies can only be read from the domain that it is set on so it will not track any data while browsing through another sites.
- Cookie
uvc
- Duration
1 year
- Description
The cookie is set by addthis.com to determine the usage of Addthis.com service.
- Cookie
ad-id
- Duration
7 months
- Description
Provided by amazon-adsystem.com for tracking user actions on other websites to provide targeted content
- Cookie
_gat_gtag_UA_116563943_1
- Duration
1 minute
- Description
Google uses this cookie to distinguish users.
- Cookie
_gid
- Duration
1 day
- Description
This cookie is installed by Google Analytics. The cookie is used to store information of how visitors use a website and helps in creating an analytics report of how the wbsite is doing. The data collected including the number visitors, the source where they have come from, and the pages viisted in an anonymous form.
Performance
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
- Cookie
YSC
Duration
Description
This cookies is set by Youtube and is used to track the views of embedded videos.
- Cookie
_gat
- Duration
1 minute
- Description
This cookies is installed by Google Universal Analytics to throttle the request rate to limit the colllection of data on high traffic sites.
Advertisement
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
- Cookie
COMPASS
- Duration
1 hour
- Description
The COMPASS cookie is used by Yahoo to deliver targeted advertising based on user's online behavior.
- Cookie
NID
- Duration
5 months
- Description
This cookie is used to a profile based on user's interest and display personalized ads to the users.
- Cookie
__Secure-YNID
- Duration
6 months
- Description
Google cookie used to protect user security and prevent fraud, especially during the login process.
- Cookie
__Secure-ROLLOUT_TOKEN
- Duration
6 months
- Description
YouTube sets this cookie to manage feature rollout and experimentation. It helps Google control which new features or interface changes are shown to users as part of testing and staged rollouts, ensuring consistent experience for a given user during an experiment.
- Cookie
yt.innertube::nextId
- Duration
never
- Description
YouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.
- Cookie
yt.innertube::requests
- Duration
never
- Description
YouTube sets this cookie to register a unique ID to store data on what videos from YouTube the user has seen.
- Cookie
VISITOR_INFO1_LIVE
- Duration
5 months
- Description
This cookie is set by Youtube. Used to track the information of the embedded YouTube videos on a website.
- Cookie
TapAd_TS
- Duration
1 month
- Description
The cookie is set by Tapad.com. The purpose of the cookie is to track users across devices to enable targeted advertising.
- Cookie
TapAd_DID
- Duration
1 month
- Description
The cookie is set by tapad.com. The purpose of the cookie is to track users across devices to enable targeted advertising
- Cookie
personalization_id
- Duration
2 years
- Description
This cookie is set by twitter.com. It is used integrate the sharing features of this social media. It also stores information about how the user uses the website for tracking and targeting.
- Cookie
uid
- Duration
1 year
- Description
This cookie is used to measure the number and behavior of the visitors to the website anonymously. The data includes the number of visits, average duration of the visit on the website, pages visited, etc. for the purpose of better understanding user preferences for targeted advertisments.
- Cookie
loc
- Duration
1 year
- Description
This cookie is set by Addthis. This is a geolocation cookie to understand where the users sharing the information are located.
- Cookie
IDE
- Duration
2 years
- Description
Used by Google DoubleClick and stores information about how the user uses the website and any other advertisement before visiting the website. This is used to present users with ads that are relevant to them according to the user profile.
- Cookie
di2
- Duration
1 year
- Description
This cookie is set by addthis.com on sites that allows sharing on social media. The cookie is used to track user behavior anonymously to generate usage trends to improve relevance to their services and advertising.
Others
Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.
- Cookie
pxcts
- Duration
session
- Description
Description is currently not available.
- Cookie
_pxttld
- Duration
session
- Description
Description is currently not available.
- Cookie
SGPBShowingLimitationDomain77659
- Duration
2 days
- Description
Description is currently not available.
- Cookie
__Secure-YEC
- Duration
past
- Description
YouTube sets this cookie to stores the user's video player preferences using embedded YouTube video
- Cookie
S
- Duration
1 hour
- Description
Used by Yahoo to provide ads, content or analytics.
- Cookie
test_cookie
- Duration
11 months
- Description
This cookie is set by doubleclick.net. The purpose of the cookie is to determine if the users' browser supports cookies.
- Cookie
sc_at
- Duration
1 year
- Description
Snapchat sets this cookie for showing relevant advertising based on the user’s movement.
- Cookie
TapAd_3WAY_SYNCS
- Duration
1 month
- Description
TapAd sets this cookie for data synchronization with advertising networks.
- Cookie
_pin_unauth
- Duration
1 year
- Description
Pinterest set this cookie to group actions for users who cannot be identified.
- Cookie
sc_anonymous_id
- Duration
9 years
- Description
Soundcloud sets this cookie to enable visitors to embed content or files on the website.
- Cookie
um
- Duration
1 year
- Description
Set by addthis.com.(Purpose not known)
- Cookie
DCRP_Categories
- Duration
4 weeks
- Description
Description is currently not available.
- Cookie
vuid
- Duration
2 years
- Description
Vimeo installs this cookie to collect tracking information by setting a unique ID to embed videos on the website.
- Cookie
X-AB
- Duration
1 day
- Description
Adobe Analytics sets this cookie in context with multi-variate testing. This is a tool used to combine or change content on the website. This allows the website to find the best variation or edition of the site.
- Cookie
YTC
- Duration
10 minutes
- Description
YouTube sets the YTC cookie to manage the embed and viewing of videos on the website.
- Cookie
sp_t
- Duration
1 month
- Description
The sp_t cookie is set by Spotify to implement audio content from Spotify on the website and also registers information on user interaction related to the audio content.
- Cookie
sp_landing
- Duration
1 day
- Description
The sp_landing is set by Spotify to implement audio content from Spotify on the website and also registers information on user interaction related to the audio content.
- Cookie
__asc
- Duration
30 minutes
- Description
Alexa Metrics sets this cookie to track and report information to the Alexa analytics service.
- Cookie
__auc
- Duration
1 year
- Description
Alexa Metrics sets this cookie to track and report information to the Alexa analytics service.
- Cookie
AWSESS
Duration
Description
Awin sets this to ensure the same kind of advertisement is not shown to the user.
- Cookie
nevercache-b39818
- Duration
session
- Description
Description is currently not available.
REJECTSave My PreferencesACCEPT
Powered by
NewsHub](/content/site-root.html)
[Premium Content](/content/2025/08/09/faqs-everything-you-need-to-know-about-ai-agents-in-2025/# "Premium Content"/index.html)
[Read our exclusive articles](/content/2025/08/09/faqs-everything-you-need-to-know-about-ai-agents-in-2025/# "Read our exclusive articles"/index.html)
[Facebook](/content/2025/08/09/faqs-everything-you-need-to-know-about-ai-agents-in-2025/# "Facebook"/index.html)
[Instagram](/content/2025/08/09/faqs-everything-you-need-to-know-about-ai-agents-in-2025/# "Instagram"/index.html)
[X](/content/2025/08/09/faqs-everything-you-need-to-know-about-ai-agents-in-2025/# "X"/index.html)
Search
NewsHub](/content/site-root.html)
NewsHub](/content/site-root.html)
Search
[Home](/content/ ""/index.html)[Editors Pick](/content/category/editors-pick/ "View all posts in Editors Pick"/index.html)[Agentic AI](/content/category/editors-pick/agentic-ai/ "View all posts in Agentic AI"/index.html)FAQs: Everything You Need to Know About AI Agents in 2025
Add as a preferred\ \ source on Google
Table of contents
- TL;DR
- 1) What is an AI agent (2025 definition)?
- 2) What can agents do reliably today?
- 3) Do agents actually work on benchmarks?
- 4) What changed in 2025 vs. 2024?
- 5) Are companies seeing real impact?
- 6) How do you architect a production-grade agent?
- 7) Main failure modes and security risks
- 8) What regulations matter in 2025?
- 9) How should we evaluate agents beyond public benchmarks?
- 10) RAG vs. long context: which wins?
- 11) Sensible initial use cases
- 12) Build vs. buy vs. hybrid
TL;DR
- Definition: An AI agent is an LLM-driven system that perceives, plans, uses tools, acts inside software environments, and maintains state to reach goals with minimal supervision.
- Maturity in 2025: Reliable on narrow, well-instrumented workflows; improving rapidly on computer use (desktop/web) and multi-step enterprise tasks.
- What works best: High-volume, schema-bound processes (dev tooling, data operations, customer self-service, internal reporting).
- How to ship: Keep the planner simple; invest in tool schemas, sandboxing, evaluations, and guardrails.
- What to watch: Long-context multimodal models, standardized tool wiring, and stricter governance under emerging regulations.
1) What is an AI agent (2025 definition)?
An AI agent is a goal-directed loop built around a capable model (often multimodal) and a set of tools/actuators. The loop typically includes:
- Perception & context assembly: ingest text, images, code, logs, and retrieved knowledge.
- Planning & control: decompose the goal into steps and choose actions (e.g., ReAct- or tree-style planners).
- Tool use & actuation: call APIs, run code snippets, operate browsers/OS apps, query data stores.
- Memory & state: short-term (current step), task-level (thread), and long-term (user/workspace); plus domain knowledge via retrieval.
- Observation & correction: read results, detect failures, retry or escalate.
Key difference from a plain assistant: agents act—they do not only answer; they execute workflows across software systems and UIs.
2) What can agents do reliably today?
- Operate browsers and desktop apps for form-filling, document handling, and simple multi-tab navigation—especially when flows are deterministic and selectors are stable.
- Developer and DevOps workflows: triaging test failures, writing patches for straightforward issues, running static checks, packaging artifacts, and drafting PRs with reviewer-style comments.
- Data operations: generating routine reports, SQL query authoring with schema awareness, pipeline scaffolding, and migration playbooks.
- Customer operations: order lookups, policy checks, FAQ-bound resolutions, and RMA initiation—when responses are template- and schema-driven.
- Back-office tasks: procurement lookups, invoice scrubbing, basic compliance checks, and templated email generation.
Limits: reliability drops with unstable selectors, auth flows, CAPTCHAs, ambiguous policies, or when success depends on tacit domain knowledge not present in tools/docs.
3) Do agents actually work on benchmarks?
Benchmarks have improved and now better capture end-to-end computer use and web navigation. Success rates vary by task type and environment stability. Trends across public leaderboards show:
- Realistic desktop/web suites demonstrate steady gains, with the best systems clearing 50–60% verified success on complex task sets.
- Web navigation agents exceed 50% on content-heavy tasks but still falter on complex forms, login walls, anti-bot defenses, and precise UI state tracking.
- Code-oriented agents can fix a non-trivial fraction of issues on curated repositories, though dataset construction and potential memorization require careful interpretation.
Takeaway: use benchmarks to compare strategies, but always validate on your own task distribution before production claims.
4) What changed in 2025 vs. 2024?
- Standardized tool wiring: converging on protocolized tool-calling and vendor SDKs reduced brittle glue code and made multi-tool graphs easier to maintain.
- Long-context, multimodal models: million-token contexts (and beyond) support multi-file tasks, large logs, and mixed modalities. Cost and latency still require careful budgeting.
- Computer-use maturity: stronger DOM/OS instrumentation, better error recovery, and hybrid strategies that bypass the GUI with local code when safe.
5) Are companies seeing real impact?
Yes—when scoped narrowly and instrumented well. Reported patterns include:
- Productivity gains on high-volume, low-variance tasks.
- Cost reductions from partial automation and faster resolution times.
- Guardrails matter: many wins still rely on human-in-the-loop (HIL) checkpoints for sensitive steps, with clear escalation paths.
What’s less mature: broad, unbounded automation across heterogeneous processes.
6) How do you architect a production-grade agent?
Aim for a minimal, composable stack:
- Orchestration/graph runtime for steps, retries, and branches (e.g., a light DAG or state machine).
- Tools via typed schemas (strict input/output), including: search, DBs, file store, code-exec sandbox, browser/OS controller, and domain APIs. Apply least-privilege keys.
- Memory & knowledge:
- Ephemeral: per-step scratchpad and tool outputs.
- Task memory: per-ticket thread.
- Long-term: user/workspace profile; documents via retrieval for grounding and freshness.
- Actuation preference: prefer APIs over GUI. Use GUI only where no API exists; consider code-as-action to reduce click-path length.
- Evaluators: unit tests for tools, offline scenario suites, and online canaries; measure success rate, steps-to-goal, latency, and safety signals.
Design ethos: small planner, strong tools, strong evals.
7) Main failure modes and security risks
- Prompt injection and tool abuse (untrusted content steering the agent).
- Insecure output handling (command or SQL injection via model outputs).
- Data leakage (over-broad scopes, unsanitized logs, or over-retention).
- Supply-chain risks in third-party tools and plugins.
- Environment escape when browser/OS automation isn’t properly sandboxed.
- Model DoS and cost blowups from pathological loops or oversize contexts.
Controls: allow-lists and typed schemas; deterministic tool wrappers; output validation; sandboxed browser/OS; scoped OAuth/API creds; rate limits; comprehensive audit logs; adversarial test suites; and periodic red-teaming.
8) What regulations matter in 2025?
- General-purpose model (GPAI) obligations are coming into force in stages and will influence provider documentation, evaluation, and incident reporting.
- Risk-management baselines align with widely recognized frameworks emphasizing measurement, transparency, and security-by-design.
- Pragmatic stance: even if you’re outside the strictest jurisdictions, align early; it reduces future rework and improves stakeholder trust.
9) How should we evaluate agents beyond public benchmarks?
Adopt a four-level evaluation ladder:
- Level 0 — Unit: deterministic tests for tool schemas and guardrails.
- Level 1 — Simulation: benchmark tasks close to your domain (desktop/web/code suites).
- Level 2 — Shadow/ proxy: replay real tickets/logs in a sandbox; measure success, steps, latency, and HIL interventions.
- Level 3 — Controlled production: canary traffic with strict gates; track deflection, CSAT, error budgets, and cost per solved task.
Continuously triage failures and back-propagate fixes into prompts, tools, and guardrails.
10) RAG vs. long context: which wins?
Use both.
- Long context is convenient for large artifacts and long traces but can be expensive and slower.
- Retrieval (RAG) provides grounding, freshness, and cost control.
Pattern: keep contexts lean; retrieve precisely; persist only what improves success.
11) Sensible initial use cases
- Internal: knowledge lookups; routine report generation; data hygiene and validation; unit-test triage; PR summarization and style fixes; document QA.
- External: order status checks; policy-bound responses; warranty/RMA initiation; KYC document review with strict schemas.
Start with one high-volume workflow, then expand by adjacency.
12) Build vs. buy vs. hybrid
- Buy when vendor agents map tightly to your SaaS and data stack (developer tools, data warehouse ops, office suites).
- Build (thin) when workflows are proprietary; use a small planner, typed tools, and rigorous evals.
- Hybrid: vendor agents for commodity tasks; custom agents for your differentiators.
13) Cost and latency: a usable model
Cost(task) ≈ Σ_i (prompt_tokens_i × $/tok)
+ Σ_j (tool_calls_j × tool_cost_j)
+ (browser_minutes × $/min)
Latency(task) ≈ model_time(thinking + generation)
+ Σ(tool_RTTs)
+ environment_steps_time
Main drivers: retries, browser step count, retrieval width, and post-hoc validation. Hybrid “code-as-action” can shorten long click-paths.
Feel free to check out our GitHub Page for Tutorials, Codes and Notebooks. Also, feel free to follow us on Twitter and don’t forget to Subscribe to our Newsletter.
Michal Sutter
Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Best 21 Low-Code and No-Code AI Tools in 2026
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Meet Memory OS: A 6-Layer Open-Source Memory Stack Built on Top of Hermes Agent
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Meet EAGLE 3.1: The Speculative Decoding Algorithm That Fixes Attention Drift in LLM Inference
- Michal Sutter
Meet OmniVoice Studio: A Local, Open-Source Alternative to ElevenLabs
- Michal Sutter
- Michal Sutter
Tencent Open-Sources TencentDB Agent Memory: A 4-Tier Local Memory Pipeline for AI Agents
- Michal Sutter
- Michal Sutter
What is a Forward Deployed Engineer: The AI Role OpenAI, Anthropic, and Google Are Hiring in 2026
- Michal Sutter
Google Introduces Gemini 3.5 Flash at I/O 2026: A Faster and Cheaper Model for AI Agents and Coding
- Michal Sutter
Upstash for Redis vs Supabase vs Neon: Which One Fits Vibe Coding Workflows in 2026?
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Next Leap to Harness Engineering: JiuwenClaw Pioneers ‘Coordination Engineering’
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Top 19 AI Red Teaming Tools (2026): Secure Your ML Models
- Michal Sutter
- Michal Sutter
Google AI Launches Gemini 3.1 Flash TTS: A New Benchmark in Expressive and Controllable AI Voice
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
A Coding Guide to Markerless 3D Human Kinematics with Pose2Sim, RTMPose, and OpenSim
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Baidu Qianfan Team Releases Qianfan-OCR: A 4B-Parameter Unified Document Intelligence Model
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Meet NullClaw: The 678 KB Zig AI Agent Framework Running on 1 MB RAM and Booting in Two Milliseconds
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
How to Build Transparent AI Agents: Traceable Decision-Making with Audit Trails and Human Gates
- Michal Sutter
[Tutorial] Building a Visual Document Retrieval Pipeline with ColPali and Late Interaction Scoring
- Michal Sutter
- Michal Sutter
Agoda Open Sources APIAgent to Convert Any REST pr GraphQL API into an MCP Server with Zero Code
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
[In-Depth Guide] The Complete CTGAN + SDV Pipeline for High-Fidelity Synthetic Data
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Google Introduces Agentic Vision in Gemini 3 Flash for Active Image Understanding
- Michal Sutter
- Michal Sutter
Microsoft Unveils Maia 200, An FP4 and FP8 Optimized AI Inference Accelerator for Azure Datacenters
- Michal Sutter
- Michal Sutter
- Michal Sutter
Tencent Hunyuan Releases HPC-Ops: A High Performance LLM Inference Operator Library
- Michal Sutter
DSGym Offers a Reusable Container Based Substrate for Building and Benchmarking Data Science Agents
- Michal Sutter
What is Clawdbot? How a Local First Agent Stack Turns Chats into Real Automations
- Michal Sutter
GitHub Releases Copilot-SDK to Embed Its Agentic Runtime in Any App
- Michal Sutter
- Michal Sutter
Zhipu AI Releases GLM-4.7-Flash: A 30B-A3B MoE Model for Efficient Local Coding and Agents
- Michal Sutter
- Michal Sutter
- Michal Sutter
Black Forest Labs Releases FLUX.2 [klein]: Compact Flow Models for Interactive Visual Intelligence
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
How Cloudflare’s tokio-quiche Makes QUIC and HTTP/3 a First Class Citizen in Rust Backends
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Nanbeige4-3B-Thinking: How a 23T Token Pipeline Pushes 3B Models Past 30B Class Reasoning
- Michal Sutter
- Michal Sutter
- Michal Sutter
From Transformers to Associative Memory, How Titans and MIRAS Rethink Long Context Modeling
- Michal Sutter
Google Colab Integrates KaggleHub for One Click Access to Kaggle Datasets, Models and Competitions
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Black Forest Labs Releases FLUX.2: A 32B Flow Matching Transformer for Production Image Pipelines
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
vLLM vs TensorRT-LLM vs HF TGI vs LMDeploy, A Deep Technical Comparison for Production LLM Inference
- Michal Sutter
- Michal Sutter
Google Antigravity Makes the IDE a Control Plane for Agentic Coding
- Michal Sutter
- Michal Sutter
- Michal Sutter
Comparing the Top 4 Agentic AI Browsers in 2025: Atlas vs Copilot Mode vs Dia vs Comet
- Michal Sutter
OpenAI Researchers Train Weight Sparse Transformers to Expose Interpretable Circuits
- Michal Sutter
Comparing the Top 6 Agent-Native Rails for the Agentic Internet: MCP, A2A, AP2, ACP, x402, and Kite
- Michal Sutter
- Michal Sutter
- Michal Sutter
Moonshot AI Releases Kosong: The LLM Abstraction Layer that Powers Kimi CLI
- Michal Sutter
Comparing Memory Systems for LLM Agents: Vector, Graph, and Event Logs
- Michal Sutter
Meet Kosmos: An AI Scientist that Automates Data-Driven Discovery
- Michal Sutter
Anthropic Turns MCP Agents Into Code First Systems With ‘Code Execution With MCP’ Approach
- Michal Sutter
Why Spatial Supersensing is Emerging as the Core Capability for Multimodal AI Systems?
- Michal Sutter
Comparing the Top 6 Inference Runtimes for LLM Serving in 2025
- Michal Sutter
OpenAI Introduces IndQA: A Culture Aware Benchmark For Indian Languages
- Michal Sutter
Comparing the Top 7 Large Language Models LLMs/Systems for Coding in 2025
- Michal Sutter
- Michal Sutter
- Michal Sutter
Comparing the Top 6 OCR (Optical Character Recognition) Models/Systems in 2025
- Michal Sutter
Anthropic’s New Research Shows Claude can Detect Injected Concepts, but only in Controlled Layers
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Google vs OpenAI vs Anthropic: The Agentic AI Arms Race Breakdown
- Michal Sutter
Liquid AI’s LFM2-VL-3B Brings a 3B Parameter Vision Language Model (VLM) to Edge-Class Devices
- Michal Sutter
- Michal Sutter
- Michal Sutter
OpenAI Introduces ChatGPT Atlas: A Chromium-based browser with a built-in AI agent
- Michal Sutter
Google AI Research Releases DeepSomatic: A New AI Model that Identifies Cancer Cell Genetic Variants
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
7 LLM Generation Parameters—What They Do and How to Tune Them?
- Michal Sutter
Meta’s ARE + Gaia2 Set a New Bar for AI Agent Evaluation under Asynchronous, Event-Driven Conditions
- Michal Sutter
Microsoft AI Debuts MAI-Image-1: An In-House Text-to-Image Model that Enters LMArena’s Top-10
- Michal Sutter
Google Open-Sources an MCP Server for the Google Ads API, Bringing LLM-Native Access to Ads Data
- Michal Sutter
What are ‘Computer-Use Agents’? From Web to OS—A Technical Explainer
- Michal Sutter
- Michal Sutter
Model Context Protocol (MCP) vs Function Calling vs OpenAPI Tools — When to Use Each?
- Michal Sutter
- Michal Sutter
- Michal Sutter
StreamTensor: A PyTorch-to-Accelerator Compiler that Streams LLM Intermediates Across FPGA Dataflows
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
MLPerf Inference v5.1 (2025): Results Explained for GPUs, CPUs, and AI Accelerators
- Michal Sutter
The Role of Model Context Protocol (MCP) in Generative AI Security and Red Teaming
- Michal Sutter
OpenAI Launches Sora 2 and a Consent-Gated Sora iOS App
- Michal Sutter
Delinea Released an MCP Server to Put Guardrails Around AI Agents Credential Access
- Michal Sutter
Anthropic Launches Claude Sonnet 4.5 with New Coding and Agentic State-of-the-Art Results
- Michal Sutter
Top 10 Local LLMs (2025): Context Windows, VRAM Targets, and Licenses Compared
- Michal Sutter
- Michal Sutter
- Michal Sutter
OpenAI Releases ChatGPT ‘Pulse’: Proactive, Personalized Daily Briefings for Pro Users
- Michal Sutter
- Michal Sutter
Vision-RAG vs Text-RAG: A Technical Comparison for Enterprise Search
- Michal Sutter
- Michal Sutter
Top 15 Model Context Protocol (MCP) Servers for Frontend Developers (2025)
- Michal Sutter
LLM-as-a-Judge: Where Do Its Signals Break, When Do They Hold, and What Should “Evaluation” Mean?
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Top Computer Vision CV Blogs & News Websites (2025)
- Michal Sutter
- Michal Sutter
MIT’s LEGO: A Compiler for AI Chips that Auto-Generates Fast, Efficient Spatial Accelerators
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
Stanford Researchers Introduced MedAgentBench: A Real-World Benchmark for Healthcare AI Agents
- Michal Sutter
- Michal Sutter
- Michal Sutter
Top 12 Robotics AI Blogs/NewsWebsites 2025
- Michal Sutter
- Michal Sutter
- Michal Sutter
What are Optical Character Recognition (OCR) Models? Top Open-Source OCR Models
- Michal Sutter
- Michal Sutter
Top 7 Model Context Protocol (MCP) Servers for Vibe Coding
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
- Michal Sutter
AI and the Brain: How DINOv3 Models Reveal Insights into Human Visual Processing
- Michal Sutter
15 Most Relevant Operating Principles for Enterprise AI (2025)
- Michal Sutter
What is AI Agent Observability? Top 7 Best Practices for Reliable AI
- Michal Sutter
Chunking vs. Tokenization: Key Differences in AI Text Processing
- Michal Sutter
- Michal Sutter
Top 20 Voice AI Blogs and News Websites 2025: The Ultimate Resource Guide
- Michal Sutter
The State of Voice AI in 2025: Trends, Breakthroughs, and Market Leaders
- Michal Sutter
- Michal Sutter
Australia’s Large Language Model Landscape: Technical Assessment
- Michal Sutter
What is Agentic RAG? Use Cases and Top Agentic RAG Tools (2025)
- Michal Sutter
The Evolution of AI Protocols: Why Model Context Protocol (MCP) Could Become the New HTTP for AI
- Michal Sutter
- Michal Sutter
What is MLSecOps(Secure CI/CD for Machine Learning)?: Top MLSecOps Tools (2025)
- Michal Sutter
- Michal Sutter
How Do GPUs and TPUs Differ in Training Large Transformer Models? Top GPUs and TPUs with Benchmark
- Michal Sutter
What is a Database? Modern Database Types, Examples, and Applications (2025)
- Michal Sutter
What is a Voice Agent in AI? Top 9 Voice Agent Platforms to Know (2025)
- Michal Sutter
- Michal Sutter
Native RAG vs. Agentic RAG: Which Approach Advances Enterprise AI Decision-Making?
- Michal Sutter
Top 10 AI Blogs and News Websites for AI Developers and Engineers in 2025
- Michal Sutter
- Michal Sutter
What is DeepSeek-V3.1 and Why is Everyone Talking About It?
- Michal Sutter
Meet South Korea’s LLM Powerhouses: HyperClova, AX, Solar Pro, and More
- Michal Sutter
Migrating to Model Context Protocol (MCP): An Adapter-First Playbook
- Michal Sutter
Hello, AI Formulas: Why =COPILOT() Is the Biggest Excel Upgrade in Years
- Michal Sutter
Emerging Trends in AI Cybersecurity Defense: What’s Shaping 2025? Top AI Security Tools
- Michal Sutter
- Michal Sutter
Master Vibe Coding: Pros, Cons, and Best Practices for Data Engineers
- Michal Sutter
Is Model Context Protocol MCP the Missing Standard in AI Infrastructure?
- Michal Sutter
What is AI Inference? A Technical Deep Dive and Top 9 AI Inference Providers (2025 Edition)
- Michal Sutter
Hugging Face Unveils AI Sheets: A Free, Open-Source No-Code Toolkit for LLM-Powered Datasets
- Michal Sutter
From Deployment to Scale: 11 Foundational Enterprise AI Concepts for Modern Businesses
- Michal Sutter
- Michal Sutter
Amazon Unveils Bedrock AgentCore Gateway: Redefining Enterprise AI Agent Tool Integration
- Michal Sutter
Top 6 Model Context Protocol (MCP) News Blogs (2025 Update)
- Michal Sutter
Top 12 API Testing Tools For 2025
- Michal Sutter
Top 10 AI Agent and Agentic AI News Blogs (2025 Update)
- Michal Sutter
- Michal Sutter
Mistral AI Unveils Mistral Medium 3.1: Enhancing AI with Superior Performance and Usability
- Michal Sutter
Case Studies: Real-World Applications of Context Engineering
- Michal Sutter
- Michal Sutter
- Michal Sutter
From 100,000 to Under 500 Labels: How Google AI Cuts LLM Training Data by Orders of Magnitude
- Michal Sutter
9 Agentic AI Workflow Patterns Transforming AI Agents in 2025
- Michal Sutter
Technical Deep Dive: Automating LLM Agent Mastery for Any MCP Server with MCP- RL and ART
- Michal Sutter
- Michal Sutter
Proxy Servers Explained: Types, Use Cases & Trends in 2025 [Technical Deep Dive]
- Michal Sutter
NVIDIA XGBoost 3.0: Training Terabyte-Scale Datasets with Grace Hopper Superchip
- Michal Sutter
MoE Architecture Comparison: Qwen3 30B-A3B vs. GPT-OSS 20B
- Michal Sutter
- Michal Sutter
Model Context Protocol (MCP) FAQs: Everything You Need to Know in 2025
- Michal Sutter
Now It’s Claude’s World: How Anthropic Overtook OpenAI in the Enterprise AI Race
- Michal Sutter
7 Essential Layers for Building Real-World AI Agents in 2025: A Comprehensive Framework
- Michal Sutter
A Technical Roadmap to Context Engineering in LLMs: Mechanisms, Benchmarks, and Open Challenges
- Michal Sutter
- Michal Sutter
- Michal Sutter
The Ultimate 2025 Guide to Coding LLM Benchmarks and Performance Metrics
- Michal Sutter
- Michal Sutter
Is Vibe Coding Safe for Startups? A Technical Risk Audit Based on Real-World Use Cases
- Michal Sutter
9 Open Source Cursor Alternatives You Should Use in 2025
- Michal Sutter
Microsoft Edge Launches Copilot Mode to Redefine Web Browsing for the AI Era
- Michal Sutter
Key Factors That Drive Successful MCP Implementation and Adoption
- Michal Sutter
How Memory Transforms AI Agents: Insights and Leading Solutions in 2025
- Michal Sutter
NVIDIA AI Releases GraspGen: A Diffusion-Based Framework for 6-DOF Grasping in Robotics
- Michal Sutter
- Michal Sutter
GitHub Introduces Vibe Coding with Spark: Revolutionizing Intelligent App Development in a Flash
- Michal Sutter
- Michal Sutter
7 MCP Server Best Practices for Scalable AI Integrations in 2025
- Michal Sutter
AI Guardrails and Trustworthy LLM Evaluation: Building Responsible AI Systems
- Michal Sutter
Top 15+ Most Affordable Proxy Providers 2025
- Michal Sutter
The Ultimate Guide to Vibe Coding: Benefits, Tools, and Future Trends
- Michal Sutter
- Michal Sutter
Maybe Physics-Based AI Is the Right Approach: Revisiting the Foundations of Intelligence
- Michal Sutter
The Definitive Guide to AI Agents: Architectures, Frameworks, and Real-World Applications (2025)
- Michal Sutter
OpenAI Introduces ChatGPT Agent: From Research to Real-World Automation
- Michal Sutter
How to Connect Google Colab with Google Drive (2025 Detailed & Updated Guide)
- Michal Sutter
50+ Model Context Protocol (MCP) Servers Worth Exploring
RELATED ARTICLES MORE FROM AUTHOR
[How to Build a QwenPaw Agent Workspace with Custom Skills, Model Providers, Console Access, and Streaming API Testing](/content/2026/06/13/how-to-build-a-qwenpaw-agent-workspace-with-custom-skills-model-providers-console-access-and-streaming-api-testing/ "How to Build a QwenPaw Agent Workspace with Custom Skills, Model Providers, Console Access, and Streaming API Testing"/index.html)
[Anthropic Disables Claude Fable 5 and Mythos 5 After US Government Order](/content/2026/06/13/anthropic-disables-claude-fable-5-and-mythos-5-after-us-government-order/ "Anthropic Disables Claude Fable 5 and Mythos 5 After US Government Order"/index.html)
[Moonshot AI Releases Kimi K2.7-Code: a Coding Model Reporting +21.8% on Kimi Code Bench v2 Over K2.6](/content/2026/06/12/moonshot-ai-releases-kimi-k2-7-code-a-coding-model-reporting-21-8-on-kimi-code-bench-v2-over-k2-6/ "Moonshot AI Releases Kimi K2.7-Code: a Coding Model Reporting +21.8% on Kimi Code Bench v2 Over K2.6"/index.html)
[A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using city2graph, OSMnx, and PyTorch Geometric](/content/2026/06/12/a-coding-implementation-on-spatial-graph-neural-networks-for-urban-function-inference-using-city2graph-osmnx-and-pytorch-geometric/ "A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using city2graph, OSMnx, and PyTorch Geometric"/index.html)
[Google Releases Gemini-SQL2: Gemini 3.1 Pro Text-to-SQL Scores 80.04% on BIRD Single-Model Leaderboard](/content/2026/06/12/google-releases-gemini-sql2-gemini-3-1-pro-text-to-sql-scores-80-04-on-bird-single-model-leaderboard/ "Google Releases Gemini-SQL2: Gemini 3.1 Pro Text-to-SQL Scores 80.04% on BIRD Single-Model Leaderboard"/index.html)
[Moonshot AI Launches Kimi Work, a Local Desktop Agent Reportedly Running on Kimi K2.6 With a 300-Sub-Agent Agent Swarm](/content/2026/06/12/moonshot-ai-launches-kimi-work-a-local-desktop-agent-reportedly-running-on-kimi-k2-6-with-a-300-sub-agent-agent-swarm/ "Moonshot AI Launches Kimi Work, a Local Desktop Agent Reportedly Running on Kimi K2.6 With a 300-Sub-Agent Agent Swarm"/index.html)
[How to Build a QwenPaw Agent Workspace with Custom Skills, Model Providers, Console Access,...](/content/2026/06/13/how-to-build-a-qwenpaw-agent-workspace-with-custom-skills-model-providers-console-access-and-streaming-api-testing/ "How to Build a QwenPaw Agent Workspace with Custom Skills, Model Providers, Console Access, and Streaming API Testing"/index.html)
Sana Hassan-June 13, 20260
In this tutorial, we implement a QwenPaw workflow that provides a practical environment for building and testing an agent-powered assistant. We install and initialize...
Asif Razzaq-June 13, 20260
shutdown followed a US government export control directive citing national security authorities. All other Anthropic models, including Opus 4.8, remain available.
[Moonshot AI Releases Kimi K2.7-Code: a Coding Model Reporting +21.8% on Kimi Code Bench...](/content/2026/06/12/moonshot-ai-releases-kimi-k2-7-code-a-coding-model-reporting-21-8-on-kimi-code-bench-v2-over-k2-6/ "Moonshot AI Releases Kimi K2.7-Code: a Coding Model Reporting +21.8% on Kimi Code Bench v2 Over K2.6"/index.html)
Asif Razzaq-June 12, 20260
Moonshot AI has open-sourced Kimi K2.7-Code under a Modified MIT license. It is a coding-focused, agentic model built on Kimi K2.6, with a 256K context window and roughly 30% lower reasoning-token usage. Moonshot reports gains over K2.6 on six benchmarks, including +21.8% on Kimi Code Bench v2. The model is available via the Kimi API and Kimi Code.
[A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using city2graph,...](/content/2026/06/12/a-coding-implementation-on-spatial-graph-neural-networks-for-urban-function-inference-using-city2graph-osmnx-and-pytorch-geometric/ "A Coding Implementation on Spatial Graph Neural Networks for Urban Function Inference Using city2graph, OSMnx, and PyTorch Geometric"/index.html)
Sana Hassan-June 12, 20260
We build an end-to-end spatial graph learning pipeline using city2graph. We collect urban POI and street network data from OpenStreetMap, with a synthetic fallback for reliability. We engineer spatial features, construct several proximity graph families, and compare how each represents the same urban environment. We then build heterogeneous and homogeneous graphs, convert them to PyTorch Geometric, and train a GraphSAGE model to predict POI categories from spatial structure.
Asif Razzaq-June 12, 20260
We look at Gemini-SQL2, the text-to-SQL capability Google Research announced on June 12, 2026. Powered by Gemini 3.1 Pro, it posted 80.04% execution accuracy on the BIRD single-model leaderboard. We explain what the score measures, how the leaderboard stacks up, and what Google has not yet disclosed. We also cover use cases and a schema-grounded implementation pattern.
[Moonshot AI Launches Kimi Work, a Local Desktop Agent Reportedly Running on Kimi K2.6...](/content/2026/06/12/moonshot-ai-launches-kimi-work-a-local-desktop-agent-reportedly-running-on-kimi-k2-6-with-a-300-sub-agent-agent-swarm/ "Moonshot AI Launches Kimi Work, a Local Desktop Agent Reportedly Running on Kimi K2.6 With a 300-Sub-Agent Agent Swarm"/index.html)
Asif Razzaq-June 12, 20260
Moonshot AI's Kimi Work is a local desktop agent for macOS and Windows. It runs a 300-sub-agent swarm, drives your logged-in browser via WebBridge, and schedules background jobs.
[Zyphra Release Zamba2-VL: Hybrid Mamba2–Transformer Vision-Language Models That Cut Time-to-First-Token by About an Order...](/content/2026/06/12/zyphra-release-zamba2-vl-hybrid-mamba2-transformer-vision-language-models-that-cut-time-to-first-token-by-about-an-order-of-magnitude/ "Zyphra Release Zamba2-VL: Hybrid Mamba2–Transformer Vision-Language Models That Cut Time-to-First-Token by About an Order of Magnitude"/index.html)
Asif Razzaq-June 12, 20260
Zyphra has released Zamba2-VL, a family of open vision-language models at 1.2B, 2.7B, and 7B parameters. The models use a hybrid Mamba2 state-space and Transformer backbone, shipping under Apache 2.0. They stay competitive with comparable Transformer VLMs while cutting time-to-first-token by about an order of magnitude.
[A Coding Implementation on MONAI for End-to-End 3D Spleen Segmentation Using UNet on Medical...](/content/2026/06/12/a-coding-implementation-on-monai-for-end-to-end-3d-spleen-segmentation-using-unet-on-medical-ct-volumes/ "A Coding Implementation on MONAI for End-to-End 3D Spleen Segmentation Using UNet on Medical CT Volumes"/index.html)
Sana Hassan-June 12, 20260
In this tutorial, we build an end-to-end 3D medical image segmentation pipeline using MONAI to segment the spleen on the Medical Segmentation Decathlon Task09...
[Perplexity Moves Deep Research Into Computer, Routing Research Subtasks Across 20+ Frontier Models For...](/content/2026/06/11/perplexity-moves-deep-research-into-computer-routing-research-subtasks-across-20-frontier-models-for-reports-decks-and-dashboards/ "Perplexity Moves Deep Research Into Computer, Routing Research Subtasks Across 20+ Frontier Models For Reports, Decks, And Dashboards"/index.html)
Michal Sutter-June 11, 20260
Deep Research now lives inside Perplexity Computer, breaking hard questions into subtasks and routing across 20+ frontier models.
[xAI Ships Grok Build Plugin Marketplace With MongoDB, Vercel, Sentry, Chrome DevTools, Cloudflare, and...](/content/2026/06/11/xai-ships-grok-build-plugin-marketplace-with-mongodb-vercel-sentry-chrome-devtools-cloudflare-and-superpowers-plugins-at-launch/ "xAI Ships Grok Build Plugin Marketplace With MongoDB, Vercel, Sentry, Chrome DevTools, Cloudflare, and Superpowers Plugins at Launch"/index.html)
Michal Sutter-June 11, 20260
Grok Build's in-terminal marketplace bundles skills, agents, hooks, and MCP servers, with commit-SHA verification on every remote plugin.
© Copyright Reserved @2025 Marktechpost AI Media Inc