There are several different types of agentic AI, all serving different purposes and bringing new capabilities to the table. First, observability software allows for AI agents to be transparent, traceable and trustworthy. Especially as this software becomes more autonomous, it is especially important for humans to understand the what and why of its actions. Agent Frameworks are the backbone of building smarter agents, supporting more complex systems moving forward. The memory sector helps develop how agents learn, remember and understand the context of an input.
There are several different types of agentic AI, all serving different purposes and bringing new capabilities to the table. First, observability software allows for AI agents to be transparent, traceable and trustworthy. Especially as this software becomes more autonomous, it is especially important for humans to understand the what and why of its actions. Agent Frameworks are the backbone of building smarter agents, supporting more complex systems moving forward. The memory sector helps develop how agents learn, remember and understand the context of an input.
Although agentic AI was previously less than 1% of enterprise software in healthcare, usage is expected to surge to 33% by 2028. This is largely because of advancements in agentic AI, now able to autonomously complete tasks and work without human input. In healthcare, this means that these agents are able to take care of back-end operations such as insurance verification, prescription refill orders or indexing inbound documents.
The team at Qualtrics compiled a list of the 100 most popular uses of AI with data on how these categories changed in popularity from 2024 to 2025. Among this huge list, we can see some patterns emerge. The most popular use for AI in 2025 is for personal and professional support. Use in this category nearly doubled from 2024 to 2025. People use AI to organize their lives, manage their time and create schedules, prepare for job interviews, plan their workouts, and even manage parenting and emotional situations. Now, some use it to simulate a conversation with deceased loved ones or as a coach to improve confidence. Overall, we can see that AI used as a therapist or counselor is the most popular use case in 2025. This is somewhat surprising and perhaps concerning since generative AI doesn’t actually think or empathize as a human. It’s a predictive text model with responses based on probability. Even so, it seems many users find it helpful to reflect and sort through their thoughts and feelings with the help of AI.
The AI revolution is already well underway, and the market for IT professionals is rapidly changing to reflect this. The majority of business leaders have identified AI skill gaps as needing to be urgently addressed and have claimed that they won’t hire employees without the necessary AI literacy. Prompt engineering is one of the most important skills to meet this requirement. It involves structuring the instructions that are fed to generative AI in a way that is clear, concise, and easily followed. Multiple iterations of a task can be avoided if prompt engineering is performed effectively.
As AI grows and develops, many countries have focused on how they should regulate its growth and use. AI offers a ton of potential for great benefits and world-changing advances, but it also carries some real risks. It’s in our best interests that governments and companies consider policies that will prevent AI from doing harm and limit what bad faith actors can do to use AI in a negative way.
In its latest event, OpenAI revealed that it is launching a
desktop app of ChatGPT, a new and faster model ‘GPT-4o,’ and bringing UI
changes to ChatGPT on web.
ChatGPT works a little differently in the desktop app. When you open it on your
desktop next to a program, ChatGPT can answer any queries related to whatever
is displayed on your screen. To ask questions, you can use the Option + Space
keyboard shortcut, as well as take and share screenshots with the app to obtain
ChatGPT’s response. Currently, the app’s availability is only limited to
ChatGPT Plus users, but it will be expanded to all users with a broader rollout
in the coming weeks.
ChatGPT has been updated with a new ‘Memory’ feature exclusively
for ChatGPT Plus subscribers, that can permanently store details about users,
such as their personal information, queries, prompts, and other customizations.
The feature was first rolled out to a limited number of people in February of
2024.
The Memory feature functions in two ways: one by being asked by the user to remember specific information, and the other by self-learning from conversations, which is akin to how algorithmic systems work in apps. Once ChatGPT saves the information, it can make conversations with users more customizable without needing any reminders.
Google is testing a new AI bot that makes conversations with
people using their speech as input. The model was developed for the purpose of
helping people practise a new language.
Google rolled out this conversational AI bot back in October of last year, but it was underdeveloped at the time as its capability was limited to providing feedback on spoken sentences. In the latest updated version, the bot can now help users practice having ongoing conversations in the language they are learning; although it currently only supports conversations in English.
As its latest major move in the world of AI, tech giant Meta
has added its AI chatbot on all of its platforms: Facebook, Instagram, WhatsApp
and Messenger (minus Threads). The chatbot is available on each of these apps
as a dedicated search bar.
Meta’s AI chatbot is powered by the company’s Llama 3 model –
Meta’s most powerful AI model yet (even better than ChatGPT), and which it
claims to be “the most intelligent AI assistant” that can be used for free. This
should automatically make Meta’s integrated AI chatbot one of the best AI
assistants out there too.
OpenAI is making its voice cloning AI model, called Voice
Engine, available to a limited number of companies and developers.
Voice Engine has been in the making since 2022 and is designed
to generate voice clones based on 15-second long reference clips. According to
OpenAI, the model was trained on “a mix of licensed and publicly available
data.” It can read out text prompts on command both in the speaker’s language
as well as other languages. It also provides the foundation for preset
voices for the text-to-speech API as well as ChatGPT’s Read Aloud feature.
Companies from a wide range of sectors are included among those with early access to Voice Engine – from education tech and storytelling to AI communication, health, and more.
Cloud collaboration and productivity platform Airtable is
launching ‘Airtable AI’ that consists of generative AI summary, categorization,
and translation features. The company has tested these features with more than
1,200 organizations and is now making them available for purchase to all its users.
AI has been proven to be an efficient integration in workspace platforms like Google Workspace and Microsoft Office – especially for the purpose of producing summaries and drafting text documents. Airtable AI is therefore likely to make Airtable an all-rounder platform, with functions dedicated to organizing teams, pushing tailored content to customers, and more.
Microsoft is releasing Copilot for OneDrive in April and has
recently revealed in a new blog post how the AI integration will work for its
file hosting platform. From finding information to summarizing and extracting it
from an extensive range of files, Copilot will basically function as your
research assistant bot in OneDrive.
The files that Copilot can work with include text documents, presentations, spreadsheets, HTML pages, PDFs, and more. In addition to generating summaries, the bot can also customize them as per the user’s command, such as only adding key points or highlights from a select part.
Adobe has launched a new prototype of its generative AI tool
‘Project Music GenAI Control.’ It is currently undergoing development with the
help of collaborative efforts by the University of California and the School of
Computer Science at Carnegie Mellon University.
The tool, like other generative AI audio tools, is designed to produce audio based on text descriptions. But there is more to it too: the ability to edit the output without having to use a separate editing software – allowing the user enhanced control over their creation. This is something that is either lacking or not sufficiently supported in other tools like Google’s MusicLM or Meta’s AudioCraft.
Microsoft has a new AI venture in development – this time in
partnership with French AI startup Mistral. It’s a multiyear partnership worth
almost $2.1 billion, where Microsoft is reported to be owning a minor stake in
the company.
As a result of the collaborative efforts between both the companies, Mistral will be offering development and deployment of its open and commercial language models to users of Microsoft’s AI platform Azure.
Google is expanding its existing partnership with Reddit to acquire
AI training data from the company that will help it adopt better ways to train AI
models.
More specifically, as a result of the partnership, Google will be able to access Reddit’s data API that will bring its users real-time content from Reddit’s platform. This will facilitate users of Google’s products in participating in Reddit communities and conversations. In turn, Reddit will have access to Google’s AI-powered service ‘Vertex AI,’ which will help the company enhance its search capabilities.
A report from Bloomberg states that Apple has advanced the
internal testing of new generative AI integrations for its Xcode programming
software, and will be making them available to third-party developers this
year.
Additionally, Apple is reported to be exploring generative
AI in consumer-facing products; such as automatic playlists in Apple Music,
slideshows in Keynote, and AI chatbot / search features for Spotlight search.
Apple’s revamped AI-powered code completion tool is similar to Microsoft’s GitHub Copilot, according to Bloomberg’s report. It applies a large language model (LLM) to predict and complete code strings, as well as generate code to test apps.
OpenAI is launching a new text-to-video AI model called ‘Sora,’
that is designed to produce photorealistic videos from text-based descriptions.
Recently, AI video generating models have started to assert
their presence in the market. We’ve got companies like Runway and Pika that
have developed their own text-to-video models. There is also Google’s Lumiere
figures that are one of OpenAI’s leading competitors.
According to OpenAI, Sora’s capabilities allow it to judge how objects exist in the physical world, as well as some complex phenomena like emotions. As a result, it can create complex scenes with multiple characters, specific types of motion, and accurate details of the subject and background.
Apple’s research department is pitching a prototype of a new generative AI animation tool ‘Keyframer,’ that enables adding motion to 2D
images with prompts.
Apple is keen on exploring large language models (LLMs) in
animation for their potential, just like in text and image generation. Earlier,
Apple introduced Human Gaussian Splats (HUGS) that creates animation-ready
human avatars from video clips, and MGIE that edits images using text prompts,
among its latest generative AI projects
In a research paper that the company published last week, it
explains that Keyframer is powered by OpenAI’s GPT4 model and collects data in
the form of Scalable Vector Graphic (SVG) files. It then produces a CSS code that
animates the image based on a text-based prompt. These prompts can be anything
that describe how the animation must look like, e.g. “make the frog jump.”
Automated transcription service Otter is launching an AI
feature called ‘AI Chat in Channels,’ to its group chat functionality ‘Channels.’
Channels work pretty much like Slack chats, where people can connect with
frequent collaborators and share transcripts with each other.
With the help of the new AI integration, groups will be able
to ask a chatbot questions related to their older meetings. The chatbot will
then gather information from all the meetings that group members have participated
in, and generate answers to the prompts asked.






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