Bonjour à tous,

Je suis actuellement stagiaire et j'utilise pour la première fois Gamma dans le cadre d’une étude de prix pour un bien immobilier. Je dois créer une présentation, et j’ai choisi Gamma car il me semblait pratique pour cela.

Mais j’ai un doute : est-ce que Gamma sert uniquement à créer des présentations visuelles, ou est-ce qu’il peut aussi m’aider à générer du contenu pertinent (par exemple : des analyses, des comparaisons de prix, des insights, etc.) ? Et si c’est possible, comment formuler au mieux mes demandes pour qu’il me donne des informations utiles ? Car pour l’instant, les réponses que j’obtiens ne sont pas très précises ou exploitables…

Je débute totalement avec cet outil, donc je suis preneuse de tout conseil ou retour d’expérience ! Merci d’avance à ceux qui prendront le temps de m’aider 🙏

Intel Corp. is poised to announce plans this week to cut more than 20% of its staff, aiming to eliminate bureaucracy at the struggling chipmaker, according to a person with knowledge of the matter.

With regard to Generative Artificial Intelligence and other digital tools used in the making of the film, the tools neither help nor harm the chances of achieving a nomination. The Academy and each branch will judge the achievement, taking into account the degree to which a human was at the heart of the creative authorship when choosing which movie to award.

Can't run Windows 11? Don't want to? There are surprisingly legal options

The chip maker is using AI throughout the software development lifecycle

🧮 Decentralization Scoring System (v1.3)

This scoring system evaluates how decentralized and self-hostable a platform is, based on four core metrics.

📊 Scoring Metrics (Total: 100 Points)

📋 Example Breakdown (Estimates)

📧 Email

• Top Provider User Share: Google ≈ 17% → Score: 30/30
• Top Provider Content Share: Google handles ≈ 17% of mail → Score: 30/30
• Self-Hosting: Server: Easy (Can leverage hundreds of email hosting options) → Score: 16/20
• Self-Hosting: Client: Easy (Thunderbird, K-9, etc.) → Score: 19/20

Total: 95/100

🐹 Lemmy

• Top Provider User Share: lemmy.world ≈ 37% → Score: 21.5/30
• Top Provider Content Share: lemmy.world hosts ≈ 37% content → Score: 21.5/30
• Self-Hosting: Server: Easy (Docker, low resource) → Score: 18/20
• Self-Hosting: Client: Good FOSS apps, web UI → Score: 18/20

Total: 79/100

🐘 Mastodon

• Top Provider User Share: mastodon.social ≈ 40% → Score: 20/30
• Top Provider Content Share: mastodon.social ≈ 45–50% content → Score: 20/30
• Self-Hosting: Server: Docker setup, moderate difficulty → Score: 15/20
• Self-Hosting: Client: Strong ecosystem (Tusky, web, etc.) → Score: 19/20

Total: 74/100

🟣 PeerTube

• Top Provider User Share: wirtube.de ≈ 14% → Score: 30/30
• Top Provider Content Share: Approximately 14% → Score: 30/30
• Self-Hosting: Server: Docker, active community, moderate resources → Score: 16/20
• Self-Hosting: Client: Web-first UI, FOSS, some mobile options → Score: 18/20

Total: 94/100

🖼 Pixelfed

• Top Provider User Share: pixelfed.social ≈ 71% → Score: 4.5/30
• Top Provider Content Share: Approximately 71% → Score: 4.5/30
• Self-Hosting: Server: Laravel-based, Docker available, some config needed → Score: 15/20
• Self-Hosting: Client: Web UI, FOSS, mobile apps in progress → Score: 18/20

Total: 42/100

🔵 Bluesky

• Top Provider User Share: bsky.social ≈ 99% → Score: 0/30
• Top Provider Content Share: Nearly all content on bsky.social → Score: 0/30
• Self-Hosting: Server: PDS hosting possible but very niche and poorly documented → Score: 4/20
• Self-Hosting: Client: Mostly official client; some 3rd party → Score: 10/20

Total: 14/100

🟠 Reddit

• Top Provider User Share: Reddit hosts 100% of user accounts → Score: 0/30
• Top Provider Content Share: Reddit hosts all user-generated content → Score: 0/30
• Self-Hosting: Server: Not self-hostable (proprietary platform) → Score: 0/20
• Self-Hosting: Client: Some unofficial clients available → Score: 3/20

Total: 3/100

How Scores are Calculated

🧑‍🤝‍🧑 How User/Content Share Scores Work

This measures how many users are on the largest provider (or instance).

• No provider > 20%: If no provider has more than 20%, it gets full 30 points.
• Between 20% and 80%: Anything in between is scored on a linear scale.
• > 80%: If a provider has more than 80%, it gets 0 points.

📊 Formula:

Score = 30 × (1 - (TopProviderShare - 20) / 60)
…but only if TopProviderShare is between 20% and 80%.
If below 20%, full 30. If above 80%, zero.

📌 Example:

If one provider has 40% of all users:
→ Score = 30 × (1 - (40 - 20) / 60) = 30 × (1 - 0.43) = 17.1 points

🖥️ How Ease of Self-Hosting Scores Work

These scores measure how easy it is for individuals or communities to run their own servers or use clients.

This looks at how technically easy it is to run your own backend (e.g., email server, Mastodon server) or User Interface (e.g., web-interface or mobile-app)

• Very Easy: One-command or setup wizard, great documentation → 18–20 points
• Moderate: Docker or manual setup, some config, active community support → 13–17 points
• Hard: Complex setup, needs regular updates or custom config, poor documentation → 6–12 points
• Very Hard or Proprietary: Little to no self-hosting support, undocumented → 0–5 points

📚 Sources

• 📧 Email W3Techs – Email Server Overview
• 🐹 Lemmy
  Fedidb – Lemmy Software Stats
• 🐘 Mastodon
  Fedidb – Mastodon Software Stats
• 🟣 PeerTube
  Fedidb – PeerTube Software Stats
• 🖼 Pixelfed
  Fedidb – Pixelfed Software Stats
• 🔵 Bluesky SoftwareMill – Bluesky’s Decentralized Architecture
• 🟥 Reddit Wikipedia - Reddit API Controversy

Footnotes

This is a work in progress and may contain mistakes. If you have ideas or suggestions for improvement, feel free to let me know.

Source: https://github.com/NoBadDays/decentralization-score/blob/main/decentralization_score_2025.04.md

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We present the Virology Capabilities Test (VCT), a large language model (LLM) benchmark that measures the capability to troubleshoot complex virology laboratory protocols. VCT is difficult: expert virologists with access to the internet score an average of 22.1% on questions specifically in their sub-areas of expertise. However, the most performant LLM, OpenAI's o3, reaches 43.8% accuracy and even outperforms 94% of expert virologists when compared directly on question subsets specifically tailored to the experts' specialites.

https://archive.ph/xILJR

Nearly a year ago, U.S. District Judge Amit Mehta ruled that Google had acted illegally to maintain a monopoly on the search engine market.

It was a decision that sent shockwaves through Silicon Valley and Washington.

In the world of digital advertising, where billions shift hands daily, a new breed of performance marketers is quietly shaping the rules from the shadows. In this rare and unfiltered conversation, Stan Sadokov — co-founder of Multilogin and a recognized expert in online anonymity and anti-detection tools — sits down with Blagoy Nikushev, the founder of Zmatic, a company providing the underground infrastructure behind many of today’s most aggressive Meta ad campaigns.

cross-posted from: https://lemm.ee/post/62035862