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Fossils of new human relative found at Maropeng

Social media played a significant role in the discovery announced this week of a new species of human relative at Maropeng near Johannesburg.

The discovery of a new species of human relative has been announced by the University of the Witwatersrand (Wits University), the National Geographic Society, the Department of Science and Technology (DST), and the National Research Foundation of South Africa (NRF).

Besides shedding light on the origins and diversity of our genus, the new species, Homo naledi, appears to have intentionally deposited bodies of its dead in a remote cave chamber, a behaviour previously thought limited to humans.

Consisting of more than 1 550 numbered fossil elements, the discovery is the single largest fossil hominin find yet made on the continent of Africa.

Social media played a significant role in finding key participants in the project, and continued to play a role in creating awareness of the expedition.

About H. naledi

The initial discovery was made in 2013 in a cave known as Rising Star in the Cradle of Humankind World Heritage Site, 50 kilometers northwest of Johannesburg, by Wits University scientists and volunteer cavers.

The fossils, which have yet to be dated, lay in a chamber about 90 meters from the cave entrance, accessible only through a chute so narrow that a special team of very slender individuals was needed to retrieve them.

So far, the team has recovered parts of at least 15 individuals of the same species, a small fraction of the fossils believed to remain in the chamber.

“With almost every bone in the body represented multiple times, Homo naledi is already practically the best-known fossil member of our lineage,” said Lee Berger, research professor in the Evolutionary Studies Institute at Wits University and a National Geographic Explorer-in-Residence, who led the two expeditions that discovered and recovered the fossils.

“The South African Strategy for the Paleosciences provides an explicit roadmap that includes government’s vision to protect, preserve and generate knowledge in this critical scientific area.  Central to the strategy is the mandate of the National Research Foundation (NRF) of SA, namely, the development of excellent human capital, and contributing to the knowledge economy through new knowledge generation. Therefore, it was natural for the NRF to be involved in this project and we are excited about its findings and we congratulate the team,” said Dr Gansen Pillay, Deputy CEO of the NRF.

A blend of primitive and human

H. naledi was named after the Rising Star cave — “naledi” means “star” in Sesotho, a South African language.

“Overall, Homo naledi looks like one of the most primitive members of our genus, but it also has some surprisingly human-like features, enough to warrant placing it in the genus Homo,” said John Hawks of the University of Wisconsin-Madison, US, a senior author on the paper describing the new species. “H. naledi had a tiny brain, about the size of an average orange (about 500 cubic centimeters), perched atop a very slender body.”

The research shows that on average H. naledi stood approximately 1.5 meters (about 5 feet) tall and weighed about 45 kilograms (almost 100 pounds).

H. naledi’s teeth are described as similar to those of the earliest-known members of our genus, such as Homo habilis, as are most features of the skull. The shoulders, however, are more similar to those of apes.

“The hands suggest tool-using capabilities,” said Dr Tracy Kivell of the University of Kent, UK, who was part of the team that studied this aspect of H. naledi’s anatomy. “Surprisingly, H. naledi has extremely curved fingers, more curved than almost any other species of early hominin, which clearly demonstrates climbing capabilities.”

This contrasts with the feet of H. naledi, which are “virtually indistinguishable from those of modern humans,” said Dr William Harcourt-Smith of Lehman College, City University of New York, and the American Museum of Natural History, who led the study of H. naledi’s feet. Its feet, combined with its long legs, suggest that the species was well-suited for long-distance walking.

“The combination of anatomical features in H. naledi distinguishes it from any previously known species,” added Berger.

Appearance of ritualised behaviour

Perhaps most remarkably, the context of the find has led the researchers to conclude that this primitive-looking hominin may have practiced a form of behaviour previously thought to be unique to humans. The fossils — which consist of infants, children, adults and elderly individuals — were found in a room deep underground that the team named the Dinaledi Chamber, or “Chamber of Stars”.

That room has “always been isolated from other chambers and never been open directly to the surface,” said Dr Paul Dirks of James Cook University in Queensland, Australia, lead author of the eLife paper on the context of the find. “What’s important for people to understand is that the remains were found practically alone in this remote chamber in the absence of any other major fossil animals.”

So remote was the space that out of more than 1,550 fossil elements recovered, only about a dozen are not hominin, and these few pieces are isolated mouse and bird remains, meaning that the chamber attracted few accidental visitors. “Such a situation is unprecedented in the fossil hominin record,” Hawks said.

The team notes that the bones bear no marks of scavengers or carnivores or any other signs that non-hominin agents or natural processes, such as moving water, carried these individuals into the chamber.

“We explored every alternative scenario, including mass death, an unknown carnivore, water transport from another location, or accidental death in a death trap, among others,” said Berger. “In examining every other option, we were left with intentional body disposal by Homo naledi as the most plausible scenario.”

This suggests the possibility of a form of ritualised behaviour previously thought to be unique to humans. (In this context, “ritualised” refers to repeated behaviour.)

‘Underground astronauts’

The fossil material was recovered in two expeditions conducted in November 2013 and March 2014, dubbed the Rising Star Expeditions. In the initial expedition, over a period of 21 days, more than 60 cavers and scientists worked together in what Marina Elliott, one of the excavating scientists, described as “some of the most difficult and dangerous conditions ever encountered in the search for human origins”.

Elliott was one of six women selected as “underground astronauts” from a global pool of candidates after Berger issued a call on social media for experienced scientist/cavers who could fit through the 18-centimeter(7-inch)-wide cave opening. Social media continued to play a role in the project, as the team shared expedition progress with a large public audience, schoolchildren and scientists.

“This was a first in the history of the field,” said Hawks, who worked with Berger to design the media outreach.

The fossils were analysed in a unique workshop in May 2014 funded by the South African DST/NRF, Wits University and National Geographic. More than 50 experienced scientists and early-career researchers came together to study and analyze the treasure trove of fossils and to compose scientific papers.

Much remains to be discovered in the Rising Star cave. “This chamber has not given up all of its secrets,” Berger said. “There are potentially hundreds if not thousands of remains of H. naledi still down there.”

The finds are described in two papers published in the scientific journal eLife and reported in the cover story of the October issue of National Geographic magazine and a NOVA/National Geographic Special.

Reference:

The papers “Homo naledi, a new species of the genus Homo from the Dinaledi Chamber, South Africa” and “Geological and taphonomic context for the new hominin species Homo naledi from the Dinaledi Chamber, South Africa” can be freely accessed online at http://dx.doi.org/10.7554/eLife.09560 and http://dx.doi.org/10.7554/eLife.09561. These articles are distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Funding:

The research was supported by Wits University, the National Geographic Society and South African DST/NRF. Ongoing exploration and conservation of the Rising Star site is supported by the Lyda Hill Foundation.

* Image courtesy of National Geographic.

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Now IBM’s Watson joins IoT revolution in agriculture

Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production

IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.

By 2050, the world will need to feed two billion more people without an increase in arable land [1]. IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.

Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”

New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.

Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.” 

The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 [2]. Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.

IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.

The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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What if Amazon used AI to take on factories?

By ANTONY BOURNE, IFS Global Industry Director for Manufacturing

Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.

At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.

If Amazon did factories

If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.

Manufacturing with knowledge

Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.

In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.

As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.

Knowledge for manufacturing

For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.

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