Intel has launched a new AI processor series for the edge, promising industrial-class deep learning inference. The new ‘Amston Lake’ Atom x7000RE chips offer up to double the cores and twice the higher graphics base frequency as the previous x6000RE series, all neatly packed within a 6W–12W BGA package.
The x7000RE series packs more performance into a smaller footprint. Boasting up to eight E-cores it supports LPDDR5/DDR5/DDR4 memory and up to nine PCIe 3.0 lanes, delivering robust multitasking capabilities.
Intel says its new processors are designed to withstand challenging conditions, enduring extreme temperature variations, shock, and vibration, and to operate in hard-to-reach locations. They offer 2x SATA Gen 3.2 ports, up to 4x USB 3.2 Gen 2 ports, a USB Type-C port, 2.5GbE Ethernet connection, along with Intel Wi-Fi, Bluetooth, and 5G platform capabilities.
Embedded, industrial, and communication
The x7000RE series consists of four SKUs, all suitable for embedded, industrial, and communication use under extended temperature conditions. The x7211RE and x7213RE have 2 cores and relatively lower base frequencies, while the x7433RE has 4 cores, and the x7835RE has 8 cores with higher base frequencies.
All four SKUs support a GPU execution unit count of either 16 or 32, and Intel’s Time Coordinated Computing and Time-Sensitive Networking GbE features. The x7000RE offer integrated Intel UHD Graphics, Intel DL Boost, Intel AVX2 with INT8 support, and OpenVINO toolkit support.
Intel says the chips will allow customers to easily deploy deep learning inference at the industrial edge and in smart cities, and “enhance computer vision solutions with built-in AI capabilities and ecosystem-enabled camera modules” as well as “capture power- and cost-efficient performance to enable latency-bounded workloads in robotics and automation.”
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Scientists sampled genomic data from 279 graves at a cemetery in Rákóczifalva, Hungary, where people of the medieval Avar culture were buried.Credit: Institute of Archaeological Sciences, Eötvös Loránd University Múzeum, Budapest, Hungary
Most people know about the Huns, if only because of their infamous warrior-ruler Attila. But the Avars, another nomadic people who subsequently occupied roughly the same region of eastern and central Europe, have remained obscure despite having assembled a sprawling empire that lasted from the late sixth century to the early ninth century. Even archaeologists have struggled to piece together their history and culture, relying on spotty and potentially biased contemporaneous chronicles that, in many cases, were authored by the Avars’ adversaries.
A deep dive into 424 genomes collected from hundreds of Avar graves is filling in crucial gaps in this story, revealing a wealth of insights into the Avars’s social structure and culture1. “These people basically didn’t have a voice in history, and we are kind of looking into them this way — through their bodies,” says Zuzana Hofmanová, an archaeogeneticist at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, and one of the study’s lead authors.
The work was published today in Nature.
Nine generations
The researchers focused on four cemeteries in Hungary that were once at the heart of the khaganate, as the former Avar empire was known. Importantly, all four sites were fully excavated, giving the researchers access to DNA from every grave and enabling them to use genetic data to map relatedness for entire Avar communities.
This effort got an important boost from a computational method called ancIBD, which can connect even distant family members on the basis of their shared chromosomal sequences2. Co-lead author Johannes Krause, an archaeogeneticist at Max Planck, says that scientists have generally struggled to reassemble DNA-based family trees that extend past third-degree relatives, such as first cousins or great-grandparents. But by using tools such as ancIBD, Krause and colleagues were able to chart much more convoluted Avar family trees, including a massive nine-generation pedigree comprising 146 family members.
The data suggest that, after migrating to Europe, the Avars retained many cultural practices from their place of origin on the northeast Asian steppes3. For example, the Avars were very strict about avoiding inbreeding. There were no observed instances of marriage between relatives — even at the level of second cousins. Krasue says that was surprising, given that unions between first cousins were not unusual during much of European history. “It’s really remarkable that they can keep track over nine generations who is related to whom, and who can have children with whom,” he says.
On the other hand, there was also limited intermarriage with non-Avar neighbors: about 20% of the genomic sequences in the sampled Avar DNA could be traced to central European ancestry.
A gold figurine excavated from an Avar burial site in Rákóczifalva, Hungary.Credit: Institute of Archaeological Sciences, Eötvös Loránd University Múzeum, Budapest, Hungary
The researchers recorded several examples of ‘levirate unions’, in which a widow married a male from the family of her deceased spouse, such as a brother. Such marital patterns were atypical in much of Europe, but were established features of Asian steppe-dwelling cultures, notes co-lead author Tivadar Vida, an archaeologist at Eötvös Loránd University in Budapest. “It was archaeologically very interesting to see the conservativism in the Avar society, lasting nine generations,” says Vida.
The Avars were also strictly patrilineal, with men acting as heads of family and daughters leaving their communities to join their husbands’ households. At the largest cemetery sampled, in the village of Rákóczifalva, Hungary, Hofmanová notes that there was only a single instance of both a mother and her adult daughter being interred.
Power play
The kinship data reveal what seems to be a shift in local political power that would have been difficult to detect with sparse DNA sampling. In the graves at Rákóczifalva, the researchers found that one male lineage predominated early in Avar history, but was displaced by a different Avar bloodline by the late seventh century. Intriguingly, archaeological evidence collected from those graves suggests that the subsequent family had different diets and burial rituals than did the displaced one, indicating that Avar culture shifted over time despite relatively modest levels of intermarriage with non-Avar individuals.
Carles Lalueza-Fox, a palaeogenomicist at the Institute of Evolutionary Biology in Barcelona, Spain, says that this work demonstrates the richness of the insights that can emerge when researchers have the opportunity and resources to broadly survey and analyse DNA at sites of historical interest. “Only this scale of analysis would allow you to obtain a reliable picture of kinship and social processes,” he says, adding that his group is now embracing a similar approach in their archaeogenomic research. “I think ancient genomics is moving toward this direction to obtain a more democratic and nuanced view of the past.”
US basketball star LeBron James has long been part of Beats’ history, during which time he’s also been known to leak upcoming products – and it looks like he may have done it again. The NBA legend was captured with what appears to be a brand new and unreleased Bluetooth speaker in a reel posted to Instagram (see below) by the LA Lakers. In it, you can clearly see the Pill-shaped speaker has a Beats logo – and it’s on a lanyard, which is something the most recent Beats Pill speaker didn’t have.
The Beats Pill Plus was killed off in January 2022, but it wouldn’t be up for consideration as one of the best Bluetooth speakers if it were still being sold today. It dated back to Apple‘s acquisition of Beats – it was the first Beats speaker to come with a Lightning port, which was Apple’s connector of choice at the time – and was considered by many to be overpriced at launch in 2015, never mind years later when Apple finally stopped selling it.
What we’d like to see in a new Beats Pill speaker
The Beats Pill Plus had a decent 12-hour battery life, but modern models go much better. One of our current picks, the Tribit Stormbox Flow, is good for 30 hours. But that’s not the biggest bit of the Beats speaker we’d expect to be upgraded. The Bluetooth of 2015 wasn’t a patch on the Bluetooth of today, and the best such speakers now deliver vastly improved sound quality through the use of newer, better codecs.
One of the best illustrations of how Bluetooth speakers have changed is when you compare our current favorite, the Sonos Roam, with the most recent Beats. The price is the same, because Sonos is another more premium brand. But that has up-to-date Bluetooth, Wi-Fi for even better streaming, multi-room audio support, Google Assistant and Alexa. It automatically switches between Bluetooth and Wi-Fi, it has automatic room tuning and it sounds fantastic.
And that’s a model that’s about to be replaced: we’re expecting to see the Sonos Roam 2 this summer with even better Bluetooth and improved voice control. That’s likely to arrive this June – so for a new Beats to be a Sonos killer it needs to be something as awe-inspiring the legend currently carrying it. We’ll find out soon enough, because if this is indeed a bit of celebrity product placement then the actual product launch can’t be too far away.
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A breast cancer cell (artificially coloured) climbs through a supportive film in a laboratory experiment.Credit: Steve Gschmeissner/SPL
Some stealthy cancers remain undetected until they have spread from their source to distant organs. Now scientists have developed an artificial intelligence (AI) tool that outperforms pathologists at identifying the origins of metastatic cancer cells that circulate in the body1. The proof-of-concept model could help doctors to improve the diagnosis and treatment of late-stage cancer, and extend people’s lives.
“That’s a pretty significant finding — that it can be used as an assistive tool,” says Faisal Mahmood, who studies AI applications in health care at Harvard Medical School in Boston, Massachusetts.
Elusive origins
To treat metastatic cancers, doctors need to know where they came from. The origin of up to 5% of all tumours cannot be identified, and the prognosis for people whose primary cancer remains unknown is poor.
One method used to diagnose tricky metastatic cancers relies on tumour cells found in fluid extracted from the body. Clinicians examine images of the cells to work out which type of cancer cell they resemble. For example, breast cancer cells that migrate to the lungs still look like breast cancer cells.
Every year, of the 300,000 people with cancer who are newly treated at the hospital affiliated with Tianjin Medical University (TMU) in China, some 4,000 are diagnosed using such images, but around 300 people remain undiagnosed, says Tian Fei, a colorectal cancer surgeon at TMU.
Tian, Li Xiangchun, a bioinformatics researcher who studies deep learning at TMU, and their colleagues wanted to develop a deep-learning algorithm to analyse these images and predict the origin of the cancers. Their results were published in Nature Medicine on 16 April.
Tumour training
The researchers trained their AI model on some 30,000 images of cells found in abdominal or lung fluid from 21,000 people whose tumour of origin was known. They then tested their model on 27,000 images and found there was an 83% change that it would accurately predict the source of the tumour. And there was a 99% chance that the source of the tumour was included in the model’s top three predictions.
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Having a top-three list is useful because it can help clinicians to reduce the number of extra — often intrusive — tests needed to identify a tumour’s origins, says Mahmood. The predictions were restricted to 12 common sources of cancer, including the lungs, ovaries, breasts and stomach. Some other forms of cancer, including those originating in the prostate and kidneys, could not be identified, because they don’t typically spread to fluid deposits in the abdomen and lungs, says Li.
When tested on some 500 images, the model was better than human pathologists at predicting a tumour’s origin. This improvement was statistically significant.
The researchers also retrospectively assessed a subset of 391 study participants some four years after they had had cancer treatment. They found that those who had received treatment for the type of cancer that the model predicted were more likely to have survived, and lived longer, than participants for whom the prediction did not match. “This is a pretty convincing argument” for using the AI model in a clinical setting, says Mahmood.
Mahmood has previously used AI to predict the origin of cancers from tissue samples2, and other teams have used genomic data. Combining the three data sources — cells, tissue and genomics — could further improve outcomes for people with metastatic cancers of unknown origins, he says.