Lifeboat Foundation

Microsoft’s Kosmos-1 can take image and audio prompts, paving the way for the next stage beyond ChatGPT’s text prompts.

Microsoft has unveiled Kosmos-1, which it describes as a multimodal large language model (MLLM) that can not only respond to language prompts but also visual cues, which can be used for an array of tasks, including image captioning, visual question answering, and more.

OpenAI’s ChatGPT has helped popularize the concept of LLMs, such as the GPT (Generative Pre-trained Transformer) model, and the possibility of transforming a text prompt or input into an output.

The bank has been testing the artificial intelligence tool with 300 advisors and plans to roll it out widely in the coming months, according to Jeff McMillan, head of analytics, data and innovation at the firm’s wealth management division.

Morgan Stanley’s move is one of the first announcements by a financial incumbent after the success of OpenAI’s ChatGPT, which went viral late last year by generating human-sounding responses to questions. The bank is a juggernaut in wealth management with more than $4.2 trillion in client assets. The promise and perils of artificial intelligence have been written about for years, but seemingly only after ChatGPT did mainstream users understand the ramifications of the technology.

The idea behind the tool, which has been in development for the past year, is to help the bank’s 16,000 or so advisors tap the bank’s enormous repository of research and data, said McMillan.

Deep Learning (DL) advances have cleared the way for intriguing new applications and are influencing the future of Artificial Intelligence (AI) technology. However, a typical concern for DL models is their explainability, as experts commonly agree that Neural Networks (NNs) function as black boxes. We do not precisely know what happens inside, but we know that the given input is somehow processed, and as a result, we obtain something as output. For this reason, DL models can often be difficult to understand or interpret. Understanding why a model makes certain predictions or how to improve it can be challenging.

This article will introduce and emphasize the importance of NN explainability, provide insights into how to achieve it, and suggest tools that could improve your DL model’s performance.

Artificial intelligence is no longer a futuristic idea. It’s already here, and it has turned out to be a powerful, disruptive force in healthcare fueling some of the most innovative diagnostic tools of today.

Let’s take a look at 7 examples where AI has started to transform healthcare!

That is the way to learn the most, that when you are doing something with such enjoyment that you don’t notice that the time passes.

March 13 (Reuters) — BuzzFeed Inc (BZFD.O) said on Monday that most of its cash and cash equivalents were held at Silicon Valley Bank (SIVB.O), which was shut down last week.

The digital media firm said it had about $56 million in cash and cash equivalents at the end of 2022.

Startup-focused lender SVB Financial Group last week became the largest bank to fail since the 2008 financial crisis, sending shockwaves through the global financial system and prompting regulators to step in to contain the fallout.

Year 2014 face_with_colon_three If black holes have infinitely small sizes and infinitely density this also means that string theory would also solve the infinitely small problem because now we know that infinitely small sizes exist and if that exists then so does infinite energy from super string essentially filling out the rest of the mystery of the God equation. This means that computers could be infinitely small aswell saving a ton of space aswell.

If you’ve wondered how big is a black hole? then you’ve come to the right place! Learn about the sizes of black holes and the multi-layered answer.

FallenKingdomReads’ list of The Top 5 Science Fiction Books That Explore the Ethics of Cloning.

Cloning is a topic that has been explored in science fiction for many years, often raising questions about the ethics of creating new life forms. While the idea of cloning has been discussed in various forms of media, such as movies and TV shows, some of the most interesting and thought-provoking discussions on the topic can be found in books. Here are the top 5 science fiction books that explore the ethics of cloning.

Alastair Reynolds’ House of Suns is a space opera that explores the ethics of cloning on a grand scale. The book follows the journey of a group of cloned human beings known as “shatterlings” who travel the galaxy and interact with various other sentient beings. The book raises questions about the nature of identity and the value of individuality, as the shatterlings face challenges that force them to confront their own existence and the choices they have made.

Its Up!

We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.

Over the past two years, we rebuilt our entire deep learning stack and, together with Azure, co-designed a supercomputer from the ground up for our workload. A year ago, we trained GPT-3.5 as a first “test run” of the system. We found and fixed some bugs and improved our theoretical foundations. As a result, our GPT-4 training run was (for us at least!) unprecedentedly stable, becoming our first large model whose training performance we were able to accurately predict ahead of time. As we continue to focus on reliable scaling, we aim to hone our methodology to help us predict and prepare for future capabilities increasingly far in advance—something we view as critical for safety.

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