​Dr. Isaac Kohane, who's both a computer scientist at Harvard and a physician, teamed up with two colleagues to test drive GPT-4, with one main goal: To see how the newest artificial intelligence model from OpenAI performed in a medical setting. 

"I'm stunned to say: better than many doctors I've observed," he says in the forthcoming book, "The AI Revolution in Medicine," co-authored by independent journalist Carey Goldberg, and Microsoft vice president of research Peter Lee. (The authors say neither Microsoft nor OpenAI required any editorial oversight of the book, though Microsoft has invested billions of dollars into developing OpenAI's technologies.) 

In the book, Kohane says GPT-4, which was released in March 2023 to paying subscribers, answers US medical exam licensing questions correctly more than 90% of the time. It's a much better test-taker than previous ChatGPT AI models, GPT-3 and -3.5, and a better one than some licensed doctors, too. 

Read the full article here.

Microsoft plans to invest $10 billion in OpenAI, the startup behind popular artificial intelligence tool ChatGPT, according to a report from Semafor.

The deal is part of a funding round with other investors involved that would value OpenAI at a whopping $29 billion, Semafor reported Tuesday, citing people familiar with the matter.

It isn’t clear whether the deal has been finalized but term sheets sent to prospective investors indicated the plan was to close the deal by the end of 2022, Semafor reported.

Microsoft will reportedly get a 75% share of OpenAI’s profits until it makes back the money on its investment, after which the company would assume a 49% stake in OpenAI.

Microsoft and OpenAI were not immediately available for comment when contacted by CNBC.

​For several weeks, the tech world has been abuzz with chatter about ChatGPT. The tool is a natural language processing model, meaning it is designed to generate text that appears as though a human wrote it.

The AI model, itself a variant of the GPT-3 family of large language models, has been used for everything from developing code to writing college essays.

A bet on ChatGPT could help Microsoft boost its efforts in web search, a market dominated by Google. The company’s Bing browser has only a small share of the global search engine market, however it is hoped the deal could help the firm chip away at Google’s dominance by offering more advanced search capabilities.

Read the full article here.

German-based biotech company BioNTech SE is set to acquire InstaDeep, a Tunis-born and U.K.-based artificial intelligence (AI) startup, for up to £562 million (~$680 million) in its largest deal yet.

Per Financial Times, the German vaccine maker intends to use InstaDeep’s machine learning to “improve its drug discovery process, including developing personalised treatments tailored to a patient’s cancer.”
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BioNTech is said to pay £362 million — a mix of cash and an undisclosed amount of BioNTech shares — upfront. The remaining £200 million is dependent on how InstaDeep performs in the future, according to the company’s statement.

Last January, InstaDeep, founded by Karim Beguir and Zohra Slim in 2014, raised $100 million in Series B financing led by Alpha Intelligence Capital and CDIB. BioNTech was among the participating investors, which also included Chimera Abu Dhabi, Deutsche Bahn’s DB Digital Ventures and Google.

The Tunis and London-based enterprise AI startup which uses advanced machine learning techniques to bring AI to applications within an enterprise environment, has offices in Paris, Tunis, Lagos, Dubai and Cape Town.

CEO Beguir, in an interview with TechCrunch last year, said InstaDeep uses reinforcement learning, a kind of machine learning that helps design optimization strategies and tackles them simultaneously. Instances where InstaDeep applies its AI tech includes helping a large shipping company to efficiently transport thousands of containers to a railway station or automate scheduling for 10,000 trains. Other examples are the design of advanced therapeutics with silicon and routing components on a printed circuit board.

Read the full article here.

• While AI-driven healthcare solutions have proven their impact and reliability, healthcare organizations struggle to achieve the desired value from their investments in AI.
• The most promising use cases are in early diagnosis and risk stratification for chronic disease, but AI also has the potential to revolutionize drug discovery and health system operations.
• AI's impact on global health depends on three enablers: usable, representative data; trustworthy design; and, scalability.

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Three seismic shifts are driving AI innovation and AI’s impact on global health. Firstly, there is the data deluge. The doubling time for medical knowledge in 1950 was 50 years. In 2020 it was 73 days. In our survey of 1,000 doctors in the US, Europe and Asia, the vast majority said they’re overwhelmed by the volume of patient data. Without technology, humans can’t keep up.

Secondly, there are novel problems. COVID-19 exacerbated existing healthcare issues, worsening an already severe doctor shortage and testing the solvency of many hospitals, among other issues. Technology must enable healthcare providers to do more with less or else patients will suffer.

Thirdly, there is a technological renaissance. Look at ChatGPT or what deep learning can do to unlock the mysteries of the universe in search of cures.

​Read the full article here.

​As the number of devices increases, the agency is looking to adapt its regulatory framework to the new technology, including faster approval of algorithm updates.

As medical devices that use artificial intelligence and machine learning appear in more hospitals and imaging labs across the U.S., new data from the Food and Drug Administration show the agency has been fielding more submissions.
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In 2022 alone, the FDA authorized 91 AI- or machine-learning-enabled medical devices, according to data released on Oct. 5. This broad category of devices can include anything from a basic algorithm to more complex machine learning tools, Michaela Miller, U.S. medtech technology and analytics practice leader for IQVIA, a North Carolina-based analytics and clinical research firm, said by email. 

MedTech Dive analyzed FDA data on all of the AI- and machine-learning-enabled devices the agency has authorized to date. Follow this link to the full article to read the five takeaways on the rise of these devices.

The age of artificial intelligence (A.I.) is finally upon us. Consumer applications of A.I., in particular, have come a long way, leading to more accurate search results for online shoppers, allowing apps and websites to make more personalized recommendations, and enabling voice-activated digital assistants to better understand us.

As impressive as these uses of A.I. are, they only hint at how this game-changing technology will be applied in business. Because the goal of business A.I. is to help the companies that drive our global economy learn from their data to become vastly more resilient, adaptive, and innovative.

We all know there is tremendous potential value in data, which continues to grow exponentially. In fact, the world is creating 2.5 quintillion bytes of data every day (that's 2.5 followed by 18 zeros). To harness that potential, companies need A.I. to make sense of the data, and hybrid cloud computing platforms that can distribute it across organizations.

​The economic opportunity behind these technologies is enormous, given that business is only about 10 percent of the way to realizing A.I.'s full potential.

By Arvind Krishna, Chairman and Chief Executive Officer, IBM

​Read the full article here.

Artificial intelligence (AI) is showing promising results in detecting breast cancer which may otherwise have been missed by radiologists, the largest study of its kind has found.

Researchers in Germany discovered that AI can correctly detect interval breast cancers, which develop in between routine screening rounds (usually 24 months in many countries) and can be missed and diagnosed as a false negative result.

In 2020, there were 2.3 million women diagnosed with breast cancer and 685 000 deaths globally, according to the World Health Organization (WHO).

The peer-reviewed study showed approximately 16 per cent of interval cancers are probably visible during a previous screening while one in five may be too subtle to the human eye and can be missed by radiologists, which is known as "minimal signs".

The findings present an opportunity to detect more cancers at a screening with AI, which may help detect breast cancer earlier.

​Read the full article here.

Increasingly, researchers are looking for ways to implement artificial intelligence into medical imaging.
There are several different cases for why a patient might need medical imaging. Whether it’s for a cardiac event, fracture, neurological condition, or thoracic complications, AI can quickly diagnose and provide treatment options.

Recently, research organizations and universities have been pursuing the expansion of AI in cancer screenings. Due to the COVID-19 pandemic, many patients chose to delay care, such as well-visits and cancer screenings, resulting in more advanced cancers.
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By implementing AI into medical imaging, the technology can enhance medical screenings, improve precision medicine, assess patient risk factors, and lighten the load for physicians.

This article looks at how AI can help in:

• Advancing Medical Screenings - By using AI in medical imaging, physicians can identify conditions much quicker, promoting early intervention.
• Improving Precision Medicine - AI can also be implemented into medical imaging to advance precision medicine. 
• Indicating and Assessing Risk - While AI can be used in medical imaging to identify current conditions impacting a patient, it can also predict the potential risk for future illnesses.

Read the full article here.​

• Federal judge says AI can’t be listed as inventor on patents
• Case is first U.S. ruling in global dispute over AI inventions

A computer using artificial intelligence can’t be listed as an inventor on patents because only a human can be an inventor under U.S. law, a federal judge ruled in the first American decision that’s part of a global debate over how to handle computer-created innovation.

Federal law requires that an “individual” take an oath that he or she is the inventor on a patent application, and both the dictionary and legal definition of an individual is a natural person, ruled U.S. District Judge Leonie Brinkema in Alexandria, Virginia.

​Read the full article here.