Hey, I'm Kartik from Albus—an AI-powered knowledge bot for your workplace.

Today at a Glance:
📢 McAfee's Project Mockingbird: A Leap in Cybersecurity
🔎 Albus's Beta Release: Direct Search with Ticketing Connectors
🛠️ The Chatbot Builder: Build your Chatbot
🏃 Albus in Action: Find benefits quickly
📝 Insights from O’Reilly’s report

Before getting started, I wanted to ask you,

McAfee's Project Mockingbird: A Leap in Cybersecurity 📢

At CES 2024, McAfee launched Project Mockingbird, a solution aimed at detecting deepfake audio.

1. Uses AI Detection: Project Mockingbird uses contextual and behavioral models to identify AI-generated audio with high accuracy.

2. Security Enhancement: Aims to protect against the rising tide of deepfake audio used in cyber crimes.

3. Operates with Precision: McAfee promises over 90% accuracy, empowering users to make informed judgments about the audio content they encounter.

With Project Mockingbird, McAfee takes a significant step in enhancing digital trust and security.

Albus's Beta Release: Direct Search with Ticketing Connectors 🔎

Albus is improving your search experience with the new beta feature of direct search using ticketing connectors.

This update is designed to streamline your information retrieval process within project management tools.

Here's what you can expect:

1. Direct Search Capability: Effortlessly search for specific items within Jira, Azure DevOps, Asana, and ClickUp, directly from Albus.

2. Focused Search Queries: For precise results, mention the connector name. For example, ask Albus "<wiki> Can you find more information about this ticket from Jira?" or "<wiki> Can you tell me the tickets assigned to Kartik in code complete in the Albus project in Azure DevOps?"

3. Limit of Four Items: Currently, you can search for up to four items, making this ideal for quick, targeted information queries rather than summarization.

Quick update on the AI world

The Chatbot Builder: Build your Chatbot 💰

Based on recent polls, there's a high interest in Chatbot Builders.

One impressive example is the Custom GPT Chatbot Builder created by Source Duty.

It's designed for ease of use and flexibility, enabling users to create chatbots for a wide range of applications, from customer service to personalized assistance.

Here is my prompt:

A feedback chatbot for a cafe can focus on collecting customer opinions on food quality and menu options, assessing satisfaction with service and ambiance, and gathering suggestions for improvements.

Note: This screenshot is a smaller snippet of overall large response

Albus in Action: Find Benefits, Quickly 🏃

Albus turns Slack into a smart helper. If you have a question, just ask, and Albus will find answers from your team's chats and files.

When Ritikaa needed help with employee benefits, Albus showed her who to talk to, all within Slack, without spending a lot of time. It's easy and quick to use.

Did you know?

Insights from O’Reilly’s report 📝

I recently came across a report from O’Reilly, which was titled Generative AI in the Enterprise, and it surveyed the users of O-Reilly.

Here are some fun stats from the report:

1. AI users say programming and data analysis are the most needed skills.

2. 26% of AI users have adopted it within the past year, but 18% already have applications in production.

3. 16% of AI users are leveraging open source models.

4. Testing for unexpected outcomes, security, safety, fairness, and privacy are top priorities.

I won’t cover all the insights the report has to offer, but I thought of sharing it as it’s a good read for anyone building in AI.

Your feedback matters!

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Thanks for reaching this far; see you next week!