5 Mind-Blowing AI Advancements You Need to Know About Now

It seems like we’ve just barely caught up with the latest AI developments that the floodgates open once again, and in comes another barrage of head-spinning updates. It really is an amazing moment for innovation, but keeping up with every tidbit can seem like a full-time job. Not to worry, though! That’s what TEAM International is here for.

This list comprises only the best in recent AI developments, from game-changing automation capabilities to the latest AI models. Dive in and get ready to have your mind blown away!

1) NVIDIA empowers you to create your own private AI model

NVIDIA, the industry leader in GPUs and veritable workhorse of the AI revolution, recently launched a demo of “Chat with RTX,” an app that lets users run an LLM chatbot internally on their PC.

You heard that right: Chat with RTX allows users to harness the power of GenAI locally on their own devices. However, one must have a PC with an RTX 30 or 40-series GPU with at least 8GB of VRAM (Sorry, Mac users).

There are several benefits to creating a local LLM chatbot:

· Since the app is run locally, Chat with RTX ensures lightning-quick results.

· No internet connection is required to use the app.

· Total discretion on training material selection and output preferences allows for creating hyper-personalized LLM models.

· Internal LLM usage ensures that a user’s data stays completely private.

Compared to externally run LLMs like ChatGPT and Gemini, these features make Chat with RTX unique and allow for some powerful behaviors. For instance, by leveraging NVIDIA’s powerful GPUs, CWR can effectively process much longer inputs than models that rely on cloud-based processing and are trained on a broader range of tasks. In other words, if you were to supply a 100-page court transcript to Chat with RTX for analysis, it could accomplish this task much more efficiently.

The app is still in its infancy, but its potential is already apparent for users who value speed, customization, and privacy.

2) Next-gen AI video generation with Sora

On February 15, OpenAI broke the internet when it unveiled the video generation capabilities of Sora, its new text-to-video AI model.

To say the videos were of Hollywood studio-grade quality is an undersell. They were more than that; they were practically life-like in their attention to detail, motion, color, lighting, and more.

Sora is still under development, but we can’t wait to see the future of video generation once it’s released to the public. Through simple text prompts, users can create videos of unparalleled quality.

Gone is the need for expensive cameras and editing software, as any combination of characters, settings, situations, and even camera angles will be within reach. The only limit will be your imagination!

3) AI implementation advances in leaps and bounds

We said 2024 would be the year of AI implementation, and so far, it has yet to disappoint!

Going beyond output-based LLM models that introduced us to AI, several companies have now integrated automation capabilities into their product lines to fantastic effect. Take Microsoft 365 Copilot, for example, where all your regular Microsoft apps have now been augmented with the power of artificial intelligence:

· Word—AI helps identify grammatical errors, typos, and stylistic inconsistencies, suggesting improvements for clearer and more concise writing.

· Excel—AI can analyze your data and suggest relevant charts, graphs, or pivot tables to visualize information in the best way.

· Outlook—AI prioritizes your emails and suggests concise and relevant replies, saving you time and effort.

In the healthcare space, companies like Paige develop artificial tools to assist medical professionals in all sorts of tasks, from more mundane work like patient information gathering and process optimization to life-saving innovations like diagnostic instruments and personalized treatment plans.

Meanwhile, companies like Siemens leverage AI to optimize production lines in the manufacturing sector. Siemens’ artificial systems analyze massive amounts of data from sensors on factory equipment in seconds, allowing for predictive maintenance. This means identifying potential equipment failures and hazardous incidents before they happen, preventing costly downtime, and ensuring smooth production processes.

Indeed, no industry is safe from the rising wave of AI. As this technology becomes more widely accessible, implementing the artificial workforce will niche down into every conceivable category.

4) The token arms race heats up

Tokens are the building blocks of information that LLM models ingest and analyze. They can be words, parts of words, or even individual characters. Artificial models have a certain threshold for the number of tokens they can process at any given time, and this constitutes a significant determinant in their ability to process information and generate outputs.

As such, Google’s recent reveal that its Gemini 1.5 model has a whopping 1.5 million token capacity has set off alarm bells for other major AI players. Details are scarce, but the previous record holder was believed to be GPT-4 with a 1 million token capacity.

As AI models seek to outdo each other, token capacity will be one of their main areas of competition. Google’s ground-breaking announcement will likely set off a token arms race, so expect to hear more impressive token capacity thresholds being offered soon.

5) Is Anthropic starting to flirt with AGI?

The latest release of Claude, Anthropics’ artificial intelligence model, has been nothing short of astounding. Its largest version, Opus, can outperform GTP-4 and Gemini Ultra on every major benchmark, like writing code and common knowledge, but that’s not even the thing that’s caught the AI world’s attention.

Recent test answers provided by Claude hint at a new level of self-awareness. When performing a needle-in-the-haystack test, Claude not only answered correctly but commented on the test, saying:

As we can see, Claude understands that it is being tested, which suggests it understands something of the larger context in which it is operating, maybe even starting to display metacognition.

This is all just speculation, of course. AI models are highly adept at simulating the appearance of human-like intelligence without actually possessing it. In any case, emergent properties in artificial intelligence models are always worth analyzing, as they might lead to previously undiscovered capabilities.

What will the future hold?

So, there you have it: 5 fantastic AI advancements as promised! As experts in automation-focused software engineering services, we’ll admit that we don’t expect the rate of artificially powered innovation to slow down anytime soon. So, we advise business owners to follow our blog or check in with us regularly on TEAM’s social media to stay abreast of all the latest AI goodness.