Microsoft announced Thursday it is teaming up with digital pathology provider Paige to build the world’s largest image-based artificial intelligence model for identifying cancer.
The AI model is training on an unprecedented amount of data that includes billions of images, according to a release. It can identify both common cancers and rare cancers that are notoriously difficult to diagnose, and researchers hope it will eventually help doctors who are struggling to contend with staffing shortages and growing caseloads.
Paige develops digital and AI-powered solutions for pathologists, which are doctors who carry out lab tests on bodily fluids and tissues to make a diagnosis. It’s a specialty that often operates behind the scenes, and it’s crucial for determining a patient’s path forward.
“You don’t have cancer until the pathologist says so. That’s the critical step in the whole medical edifice,” Thomas Fuchs, co-founder and chief scientist at Paige, told CNBC in an interview.
But despite pathologists’ essential role in medicine, Fuchs said their workflow has not changed much in the last 150 years. To diagnose cancer, for instance, pathologists usually examine a piece of tissue on a glass slide under a microscope. The method is tried and true, but if pathologists miss something, it can have dire consequences for patients.
As a result, Paige has been working to digitize the pathologists’ workflow to improve accuracy and efficiency within the specialty.
Doctors working with Paige technology
Source: Paige
The company has received approval from the Food and Drug Administration for its viewing tool FullFocus, which allows pathologists to examine scanned digital slides on a screen instead of relying on a microscope. Paige also built an AI model that can help pathologists identify breast cancer, colon cancer and prostate cancer when it appears on the screen.
Digital pathology is costly
Paige is the only company that has received FDA approval for pathologists to use its AI as a secondary tool for identifying prostate cancer, and CEO Andy Moye said this is likely in part because of barriers related to storage costs and data collection.
Digitizing a single slide can require over a gigabyte of storage, so the infrastructure and costs associated with large-scale data collection balloon quickly. Fuchs said the storage costs can be inhibiting for smaller health systems, which is why wealthy academic centers have historically been the only organizations that can afford to invest in digital pathology.
Paige spun out of the Memorial Sloan Kettering Cancer Center in New York in 2017 and has a “fantastic wealth of data,” according to Moye, which is why the company was able to build its own AI-powered solutions in the first place. To put the scale in perspective, Paige has 10 times more data than Netflix, including all the shows and movies that exist on the platform.
But in order to expand its operations and build an AI tool that can identify more cancer types, Paige turned to Microsoft for help. Over the past year and a half, Paige has been using Microsoft’s cloud storage and supercomputing infrastructure to build an advanced new AI model.
Paige’s original AI model used more than 1 billion images from 500,000 pathology slides, but Fuchs said the model the company has built with Microsoft is “orders of magnitude larger than anything out there.” The model is training on 4 million slides to identify both common and rare cancers, which can be difficult to diagnose. Paige said it is the largest computer vision model that has ever been announced publicly.
“Until ChatGPT got released, no one really understood how this is going to impact their lives. I would argue this is very similar for cancer patients going forward,” Moye said. “This is sort of a groundbreaking, land-on-the-moon kind of moment for cancer care.”
Moye added that the company is thinking of ways to incorporate predictive modeling to give pathologists and patients easy access to information about their biomarkers and genomic mutations down the line.
Desney Tan, vice president and managing director of Microsoft Health Futures, said Microsoft’s infrastructure is a key component of the partnership, but that the company is also working to develop the new algorithms, detection and diagnostics that Paige is hoping to deliver in the next couple of years.
He added that though the technology is powerful, it’s meant to enrich pathologists, not replace them.
“We think of these AI implements, these technologies, as tools, really just as the stethoscope is a tool, just as the X-ray machine is a tool,” Tan told CNBC in an interview. “AI is a tool that is to be wielded by a human.”
On Thursday, Paige and Microsoft will publish a paper on the model through Cornell University’s preprint server arXiv. The paper quantifies the impact of the new model compared with existing models, and Fuchs said it outperforms anything that has been built in academia up to this point.
But the preprint is just the first step of a much longer journey. Paige wanted to make the research available to the broader community while it is under peer review, and the company intends to submit to the scientific journal Nature. The process can take months, if not longer. Paige also has years of work ahead before it will be able to roll the model out as a product — including thorough testing and collaboration with regulators to ensure it is safe and accurate.
Ultimately, Fuchs said the AI model will solve the storage problem for health systems, while also helping pathologists work through cases and arrive at a diagnosis more quickly. For some patients, it could mean the difference between waiting two days and two weeks to find out what’s wrong.
“The more you go away from academic medical centers, especially in community clinics where pathologists are completely overwhelmed across all cancer types with so many cases, there, the impact is quite drastic,” Fuchs said. “That really helps to democratize access to health care in these places.”
A logo hangs on the building of the Beijing branch of Semiconductor Manufacturing International Corporation (SMIC) on December 4, 2020 in Beijing, China.
After trading on Thursday, the company reported a first-quarter revenue of $2.24 billion, up about 28% from a year earlier. Meanwhile, profit attributable to shareholders surged 162% year on year to $188 million.
However, both figures missed LSEG mean estimates of $2.34 billion in revenue and $225.1 million in net income, as well as the company’s own forecasts.
During an earnings call Friday, an SMIC representative said the earnings missed original guidance due to“production fluctuations” which sent blended average selling prices falling. This impact is expected to extend into the second quarter, they added.
For the current quarter, the chipmaker forecasted revenue to fall 4% to 6% sequentially. Gross margin is also expected to fall within the range of 18% to 20%, compared to 22.5% in the first quarter.
Still, the first quarter saw SMIC’s wafer shipments increase by 15% from the previous quarter and by about 28% year-on-year.
In the earnings call, SMIC attributed that growth to customer shipment pull in, brought by changes in geopolitics and increased demand driven by government policies such as domestic trade-in programs and consumption subsidies.
In another positive sign for the company, its first-quarter capacity utilization— the percentage of total available manufacturing capacity that is being used at any given time— reached 89.6%, up 4.1% quarter on quarter.
“SMIC’s nearly 90% utilization rate reflects strong domestic demand for semiconductors, likely driven by smartphone and consumer electronics production,” said Ray Wang, a Washington-based semiconductor and technology analyst, adding that the demand was also reflected in the company’s strong quarterly revenue growth.
Meanwhile, the company said in the earnings call that it is “currently in an important period of capacity construction, roll out, and continuously increasing market share.”
However, SMIC’s first-quarter research and development spending decreased to $148.9 million, down from $217 million in the previous quarter.
Amid increased demand, it will be crucial for SMIC to continue ramping up their capacity, Simon Chen, principal analyst of semiconductor manufacturing at Informa Tech told CNBC.
SMIC generates most of its revenue from older-generation semiconductors, often referred to as “mature-node” or “legacy” chips, which are commonly found in consumer electronics and industrial equipment.
The state-backed chipmaker is critical to Beijing’s ambitions to build a self-sufficient semiconductor supply chain, with the government pumping billions into such efforts. Over 84% of its first-quarter revenue was derived from customers in China.
“The localization transformation of the supply chain has been strengthened, and more manufacturing demand has shifted back domestically,” a representative said Friday.
However, chip analysts say the chipmaker’s ability to increase capacity in advance chips — used in applications that demand higher levels of computing performance and efficiency at higher yields — is limited.
This is due to U.S.-led export controls, which prevent it from accessing some of the world’s most advanced chip-making equipment from the Netherlands-based ASML.
Nevertheless, the chipmaker appears to be making some breakthroughs. Advanced chips manufactured by SMIC have reportedly appeared in various Huawei products, notably in the Mate 60 Pro smartphone and some AI processors.
In the earnings call, the company also said it would closely monitor the potential impacts of the U.S.-China trade war on its demand, noting a lack of visibility for the second half of the year.
Phelix Lee, an equity analyst for Morningstar focused on semiconductors, told CNBC that the impacts of U.S. tariffs on SMIC are limited due to most of its revenue coming from Chinese customers.
While U.S. customers make up about 8-15% of revenue on a quarterly basis, the chips usually remain and are consumed in Chinese products and end users, he said.
“There could be some disruption to chemical, gas, and equipment supply; but the firm is working on alternatives in China and other non-U.S. regions,” he added.
SMIC’s Hong Kong-listed shares have gained over 32.23% year-to-date.
Close-up of a hand holding a cellphone displaying the Amazon Pharmacy system, Lafayette, California, September 15, 2021.
Smith Collection | Gado | Getty Images
Amazon is expanding its online pharmacy to fill prescription pet medications, the company announced Thursday.
The company said it has added “hundreds of commonly prescribed pet medications” to its U.S. site, ranging from flea and tick solutions to treatments for chronic conditions.
Prescriptions are purchased via Amazon’s storefront and must be approved by a veterinarian. Online pet pharmacy Vetsource will oversee the dispensing and delivery of medications, said Amazon, adding that items are typically delivered within two to six days.
Amazon launched its digital drugstore in 2020 with the added perk of discounts and free delivery for Prime members. The company has been working to speed up prescription shipments over the past year, bringing same-day delivery to a handful of U.S. cities. Last October, Amazon set a goal to make speedy medicine delivery available in nearly half of the U.S. in 2025.
The new pet medication offerings puts Amazon into more direct competition with online pet pharmacy Chewy, as well as Walmart, which offers pet prescription delivery.
Amazon Pharmacy is part of the company’s growing stable of healthcare offerings, which also includes One Medical, the primary care provider it acquired for roughly $3.9 billion in July 2022. Amazon’s online pharmacy was born out of the company’s 2018 acquisition of online pharmacy PillPack.
Coinbase agreed to acquire Dubai-based Deribit, a major crypto derivatives exchange, for $2.9 billion, the largest deal in the crypto industry to date.
The company said Thursday that the cost comprises $700 million in cash and 11 million shares of Coinbase class A common stock. The transaction is expected to close by the end of the year.
Shares of Coinbase rose nearly 6%.
The acquisition positions Coinbase as an international leader in crypto derivatives by open interest and options volume, Greg Tusar, vice president of institutional product, said in a blog post – which could allow it take on big players like Binance. Coinbase operates the largest marketplace for buying and selling cryptocurrencies within the U.S., but has a smaller share of the global crypto market, where activity largely takes place on Binance.
Deribit facilitated more than $1 trillion in trading volume last year and has about $30 billion of current open interest on the platform.
“We’re excited to join forces with Coinbase to power a new era in global crypto derivatives,” Deribit CEO Luuk Strijers said in a statement. “As the leading crypto options platform, we’ve built a strong, profitable business, and this acquisition will accelerate the foundation we laid while providing traders with even more opportunities across spot, futures, perpetuals, and options – all under one trusted brand. Together with Coinbase, we’re set to shape the future of the global crypto derivatives market.”
Tusar also noted that Deribit has a “consistent track record” of generating positive adjusted EBITDA the company believes will grow as a combined entity.
“One of the things we liked most about this deal is that it’s not just a game changer for our international expansion plans — it immediately diversifies our revenue and enhances profitability,” Tusar told CNBC.
The deal comes at a time when the crypto industry is riding regulatory tailwinds from the first ever pro-crypto White House. Support of the industry has fueled crypto M&A activity in recent weeks. In March, crypto exchange Kraken agreed to acquire NinjaTrader for $1.5 billion, and last month Ripple agreed to buy prime broker Hidden Road.
Don’t miss these cryptocurrency insights from CNBC Pro: