The video shows Zuckerberg wearing a blurred-out mixed reality headset and showing some examples of what users can do with the device, dubbed Project Cambria. In the video, he plays with a cartoon character that looks similar to a character shown in a Meta video released last October.

While the earlier video shows grey environments, the new video showcases the headset’s ability to have more detailed colour in mixed reality environments, which Zuckerberg called “full colour passthrough”.

Zuckerberg said the demo was powered by Meta’s Presence Platform, which was first announced last year as a way for developers to build mixed reality experiences. The company said this introduced a number of capabilities such as passthrough, spatial anchors and scene understanding to create more realistic mixed reality.

The Meta boss added that a mixed reality demo app, called the World Beyond, will be available for Quest 2 headset users from the App Lab soon.

“It’s even better with full colour passthrough and the other advanced technologies we’re adding to Project Cambria,” Zuckerberg said in a Facebook post yesterday (12 May).

In the video, he talks about how the headset can be used for gaming, exercise and work purposes. His mixed reality examples included pulling up a virtual workstation wherever you are or fitness training with a virtual instructor.

Meta CTO Andrew Bosworth said on Twitter that developers will be able to use the full set of Presence Platform tools with the next software development kit coming next week, including a recently updated hand-tracking API.

Bosworth added that the mixed reality experiences currently being developed on the Quest 2 will “now look even better with Cambria’s advanced technologies”. He mentioned examples such as new sensors, higher-resolution cameras and “active depth sensing”.

“I’m excited at the use cases these experiences will unlock across productivity, social and so much more, giving us a glimpse of what’s possible in the metaverse,” Bosworth said.

Last month, Meta recorded a first-quarter loss of nearly $3bn in its Facebook Reality Labs division, which handles the augmented and virtual reality operations of the company.

When the tech giant changed its name last year to show its commitment to the concept of the metaverse, it estimated that investment in this area would be $10bn for 2021 alone, with more to come in the next several years.

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The representative group for the Irish wind energy industry said this is a 7pc increase compared to April 2021 and is the most power ever provided by wind in the month of April.

Wind Energy Ireland added that it follows a strong first quarter of 2022, where wind provided around 39pc of Ireland’s electricity.

“Every month wind energy is cutting our carbon emissions and helping to insulate Irish consumers from the worst effects of our dependence on expensive imported gas,” Wind Energy Ireland CEO Noel Cunniffe said.

“Every new windfarm and solar farm connecting to the electricity system helps to make Ireland more energy independent.”

The Wind Energy Ireland report said the volume of wind energy produced in April helped to push down the average wholesale price of electricity to €218.26, a reduction from the record high costs in March.

However, it added that this is still a 155pc increase in price compared to April 2021, reflecting Ireland’s reliance on expensive imported fossil fuels.

“We need to accelerate the development of clean, cheap, renewable energy to push fossil fuels out of the electricity market,” Cunniffe said.

“Our planning system must be reformed and properly resourced to ensure that the renewable energy projects needed by the Climate Action Plan can get properly, but quickly, examined and we can move forward with getting those projects built.”

Wind Energy Ireland has been calling on Government to take increased measures to help develop Ireland’s offshore windfarms, a move that could present an economic opportunity as well as an environmental one.

Ireland has set a goal to generate 5GW of offshore wind energy by 2030, which could more than double the country’s current onshore and offshore wind power capacity.

But some in the industry have called on the Government to increase its 2030 wind ambitions. SSE Renewables director of development Maria Ryan told the Government earlier this year that it “shouldn’t settle for 5GW by the end of the decade”.

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The social media giant said it is sharing access to both the pretrained models and the code needed to train and use them. It added that this will allow for “more community engagement in understanding this foundational new technology”.

“Access to the model will be granted to academic researchers, those affiliated with organisations in government, civil society and academia, along with industry research laboratories around the world,” Meta AI said in a blogpost yesterday (3 May)

Large language models are natural language processing (NLP) systems that are trained on a massive volume of text. These models are able to answer reading comprehension questions, solve basic maths problems and generate text.

Meta said full research access to large language models is usually restricted to a “few highly resourced labs”, which hinders efforts to increase their “robustness” and remove issues such as bias and toxicity within the models.

“For AI research to advance, the broader scientific community must be able to work together with cutting-edge models to effectively explore their potential while also probing for their vulnerabilities at the same time,” the company said.

“Meta AI believes that collaboration across research organisations is critical to the responsible development of AI technologies.”

The social media company said it designed its model – called OPT-175B – to be energy efficient and it was trained using roughly 14pc of the carbon footprint used to train OpenAI’s GPT-3 model.

Meta also said it is releasing a suite of “smaller-scale baseline models”, trained on the same dataset and using similar settings as OPT-175B.

Meta has been investing in AI research for some time. In February the company shared some of the AI research projects it is focused on, including universal speech translation, AI that can learn like a human and a more conversational AI assistant.

In January, Meta also revealed that its AI research team has been working for years on a supercomputer that could be the world’s “largest and fastest” when fully built out, which it hoped to achieve by mid-2022.

Meta isn’t the only company looking into large language models. Last October, tech giants Microsoft and Nvidia teamed up to create a language model with 105 layers and 530bn parameters, three times as many parameters as OpenAI’s GPT-3.

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The pilot aimed to see how autonomous vehicles work with public transportation networks and to collect feedback from users. It was part of the EU-funded SHOW project, which is investigating how autonomous vehicles could work within urban transportation networks.

Two self-driving Toyota Proace vehicles were used as feeder traffic for a tram line in the city of Tampere in Finland. During the pilot exercise, the vehicles encountered extreme weather conditions such as temperatures below 20 degrees Celsius, heavy snowfalls and slippery roads.

“Of course, in Finland, snowing is everyday life in the wintertime,” Sensible 4 CBO Jussi Suomela said. “This time it reached almost an extreme level as there were piles of snow on the way and snowploughs had a hard time keeping the roads open.”

Two self-driving Toyota Proace vehicles were used during the pilot. Image: Sensible 4

Sensible 4 is developing software for last-mile autonomous vehicles in all weather conditions.

The tech company said it learned how freezing rain can affect the vehicle hardware, how to adjust to alternate-side parking and how to adapt to snowploughing tracks that are far from bus stops.

“This pilot was valuable for understanding the customer and end-user needs better, including especially the accessibility aspects,” Suomela said. “The weather was exceptionally snowy but the software and vehicles performed well and we were able to collect important test data of the extreme conditions and experience of the challenging weather.”

Sensible 4 said the passenger feedback was positive overall and mainly focused on improving accessibility for people with disabilities.

Mika Kulmala, project manager for the city of Tampere, said the self-driving vehicles “ran smoothly and felt safe”. He added that he can see these types of vehicles being used in the future to complement public transport networks for certain routes.

“We still need more testing to ensure the reliability in production use, and that the service either brings cost-saving in the areas they are being used or gives better service level to the population with the same costs,” Kulmala said.

Self-driving cars have seen advancements in leaps and bounds in recent years. Last month, the UK revealed planned changes to its highway code to pave the way for fully self-driving cars to hit the roads as soon as the second half of this year.

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We will likely see gas supplies drawn into the economic conflict in the coming months as Russia attempts to prop up the ruble by forcing European nations to alter existing contract payment agreements.

While it is unlikely that Russia will cut supplies in the long-term, given that oil and gas exports make up approximately 40pc of the country’s GDP, it is likely that restricted supplies will be used to damage the European economy.

Race for renewables

Many have suggested that this further supports a rapid transition to renewables. However, Ireland’s main move towards renewables is based on wind power generation.

Wind power generation has typically been supported by gas power plants. These gas power plants can come online quickly when demand peaks or when calmer winds reduce production. They are also comparatively cleaner than coal power plants.

One alternative to burning natural gas would be to burn hydrogen. Existing gas plants could be refitted to run on hydrogen, but there are numerous challenges that must first be tackled if this is to be long-term solution for Irish energy security.

Not all hydrogen is created equal

There are two primary types of hydrogen that are commonly referenced when considering grid energy needs: blue and green hydrogen. The distinction is based on how they are produced and their environmental impacts.

Blue hydrogen is produced from natural gas and fossil fuel companies have lobbied extensively to have it included as a stepping stone away from fossil fuels and towards a net zero energy system. This type of hydrogen is created by reforming methane that is present in natural gas using a steam-based process.

However, a recent study suggests that blue hydrogen is even worse for the environment than simply using the natural gas from which it is made from to produce electricity. Critically, it also requires natural gas to be produced, and so offers little security or energy independence for Ireland.

Green hydrogen is produced by electrolysis. In this process, electricity is used to split water (H2O) into oxygen and hydrogen. This hydrogen is then pressurised in a tank and can later be burnt in existing gas power plants. In order for this gas to be considered green hydrogen it must be produced using renewable energy.

In many ways, this could potentially meet the greatest challenge of a primarily wind-based energy grid: energy storage.

When excess energy is being produced by wind farms, hydrogen production plants could begin to create and store hydrogen. When energy demand is at its highest, gas power plants running on green hydrogen could come online to help balance the grid.

With considerable investment in both hydrogen manufacture and storage these plants could also support the national grid for extended low-wind periods. Long-term, we could begin to export renewable energy to the UK through existing gas or grid connections.

Too good to be true?

If this system could solve our problems then why isn’t everyone doing it? There are a few reasons.

Firstly, there are not many countries that have the potential for wind energy production that Ireland has. Secondly, the technology required to produce hydrogen at this type of industrial scale is still in development. Finally, it comes down to cost.

We have had the luxury of relatively cheap natural gas energy for a long time. To build the infrastructure required to reach energy independence, we will have to dedicate a huge amount of our national resources towards these efforts in the coming decades.

In 2020, 57.1pc of our electricity was generated using gas while 22pc was generated using wind. When we create green hydrogen using electrolysis, approximately 20pc of the initial energy is lost due to efficiency. A further 50pc of the remaining energy would be lost when this hydrogen is burned in a gas power plant. Using this method, only 40pc of the initial electricity generated from wind ends up in our grid. In the simplest terms, if we wanted to completely replace natural gas for electricity generation with hydrogen that was manufactured using wind energy, we would need to increase wind energy production in Ireland by approximately 650pc.

This would not include other fossil fuels which contributed an additional 5pc in terms of electricity production in 2020. It also would not include the additional electricity required if we are to transition the national fleet towards electric propulsion or gas currently used for heating.

The manufacturing and storage infrastructure would also require considerable development. Hydrogen is less energy dense than natural gas so we would need much larger tanks. In order to create a secure grid we would need very large reserves, compared to current natural gas reserves, in order to meet demand in the event of low wind conditions.

Long-term vision

Green hydrogen will likely play a part in our national grid in the future. As a means of energy storage, it has considerable potential.

However, it is extremely unlikely that we will be capable eliminating our dependence on natural gas as a significant energy source within the next decade. Even our most ambitious wind energy targets fall well short of what would be required.

Despite these challenges, the urgent need to move to renewable energy sources remains. In the short-term we are beginning to understand the need for energy security and independence.

As we now recognise the danger of a weaponised energy supply, it is critical that we also recognise the longer-term threat of the climate crisis and the devastation that complacency will lead to.

There will be no easy answers to the challenges that we face, but long-term vision that goes beyond electoral cycles has the potential to benefit our society enormously in the coming decades.

By Dr Jason Power

Dr Jason Power is an engineering lecturer and course director at University of Limerick.

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The Millvale solar farm was officially opened today (29 April) by Minister for the Environment, Climate and Communications Eamon Ryan, TD.

Millvale is located near Ashford in Co Wicklow and was developed by renewable energy company Neoen under the Government’s Renewable Electricity Support Scheme (RESS).

RESS is a competitive, auction-based scheme that invites renewable electricity projects to bid for capacity and receive a guaranteed price for the electricity they generate. The first RESS projects were approved in 2020, while the results of the second scheme are due in mid-June.

The Millvale site is the first of many solar projects to reach commercial operation under RESS-1.

It occupies 25 hectares and has 33,600 solar modules, which is enough to power around 3,600 homes every year and potentially avoid 4,800 tonnes in CO2 emissions.

Millvale is the one of three sites run by Neoen that secured support under the first RESS, with the other two being Hilltown in Co Meath and Hortland in Co Kildare. These two solar farms are still under construction.

“This the first of many solar projects expected to energise under the RESS this year,” Ryan said.

“It’s a key starting point on our journey, under the Climate Action Plan, to install up to 2.5GW of solar energy on the electricity system by 2030.”

The Irish Solar Energy Association welcomed the opening of the solar farm. It CEO Conall Bolger said that solar “must and will be a major part” of Ireland’s decarbonisation plans. “2022 will be the year where solar arrives in Ireland in a significant way,” he added.

Cyril Perrin, MD of Neoen Ireland, said the company was delighted by the speed at which it was able to deliver the Millvale project.

“The three new plants provide a solid foundation for actively pursuing further solar, wind and storage projects to drive our growth in Ireland,” he added.

French company Neoen has had teams in Ireland since 2019 and also operates eight windfarms in the country with a combined capacity of 53.4MW.

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In a study, the research team said machine learning systems usually find it difficult to understand object orientations. For example, a robot can be trained to pick up a specific item – but if the object is placed at a different angle, it is perceived as a completely new scenario by the robot.

To deal with this challenge, the researchers said they created a new type of neural network model called a neural descriptor field (NDF), which can learn the geometry of classes of items.

Using this NDF model, the team was able to teach a robot a new skill of picking up a never-before-seen object with only a few physical examples.

“Our major contribution is the general ability to much more efficiently provide new skills to robots that need to operate in more unstructured environments where there could be a lot of variability,” co-lead author of the paper Anthony Simeonov said.

“The concept of generalisation by construction is a fascinating capability because this problem is typically so much harder.”

With the help of a depth camera, the NDF model was able to compute the geometric representation for a specific item using a 3D point cloud, which is a set of coordinates in three dimensions.

The model was also designed with a property called equivariance. This means that if the model is shown an image of a mug and then another image of the mug on its side, it understands that the second mug is the same object that has been rotated.

“This equivariance is what allows us to much more effectively handle cases where the object you observe is in some arbitrary orientation,” Simeonov said.

The researchers said their new method had a success rate of 85pc on pick-and-place tasks in testing, while the best baseline comparisons could only achieve 45pc. Success in these tests meant picking up a new object and placing it on a target location. Within 10 to 15 minutes, the robot was also ready to perform a new pick-and-place task.

While these tests were seen to be a success, researchers noted that this current method only works for particular object categories. For example, a robot that is trained to pick up mugs won’t be able to pick up headphones, since the shape is too different to what the robot was trained on.

“In the future, scaling it up to many categories or completely letting go of the notion of category altogether would be ideal,” Simeonov said.

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Genç studied computer engineering at the Izmir University of Economics in Turkey, before completing her MSc with a focus on information visualisation for biological pathways at Bilkent University. In 2019, she obtained her PhD working in the optimisation and decision analytics research group at Insight.

More recently, she became the Ireland ambassador for Women in AI, a global organisation looking to close the gender gap in this area of tech.

‘There should be more focus on explaining to the end users the reasons behind decisions taken by AI systems’
^{– DR BEGÜM GENÇ}

Can you tell us about the research you’re currently working on?

I am mostly active in two areas: algorithm design and AI ethics. The former emanates from my passion for designing AI models for quickly, correctly and responsibly solving problems that a human would need months or years to solve to the same quality.

The latter focuses on assessing different AI applications – such as AI in healthcare, intelligent cities, AI in human resource management – and identifying risks and working with the developers on how to address the underlying issues.

Some problems I look at can be found in many places in our daily lives, from delivering parcels to customers to creating ideal timetables at schools. Responsible development on these problems can take different forms such as explaining why a solution is presented as the best one, ensuring the proposed solution does not discriminate against any group, that it is robust to unexpected events, etc.

In your opinion, why is your research important?

I strongly believe that AI should be developed only to be used for the good of people. It should enhance people’s daily lives by carrying out the most tedious tasks and should not harm people in any way. My research is focusing on exactly these aspects.

With the increasing access to resources, we see many self-taught developers designing AI products. It is heartbreaking to see that many developers are not familiar with responsible design principles. They are not designing to harm, but they are designing products that may potentially cause harm and they are not aware of it.

To me, it is essential to incorporate the ethical dimension in the design phase of an algorithm.

What inspired you to become a researcher?

Having been raised by a family of engineers, mathematicians and academics, I had a natural inclination towards research and science. When I was a child, my family was often referring me to the big old encyclopaedias for questions that I had. I was always encouraged to search, read and find answers to my questions.

Back then, this was a game to me. So I became more and more curious about everything. Later on, it became a passion and eventually my profession. One of my favourite activities as a child was to build circuits and other structures with my older brother.

What are some of the biggest challenges you face as a researcher in your field?

I consider myself very fortunate to have very supportive supervisors who have also acted as great mentors throughout my research career.

However, being a woman working in the AI field was not (and is not) always natural and easy. I often needed to ask for support from male colleagues to reiterate my words so that my ideas could be heard. Similarly, often I was the only woman in the class or in the office, which gives the sense of ‘not belonging’.

Then, when you get more senior in research in academia, other challenges arise. For instance, challenges around building work-life balance in academia is often underestimated. You often find yourself attending meetings, writing reports or projects and lecturing during the day, and doing research in the evening.

If you wish to prioritise your family time in the evening, or if you have some caring responsibilities, you will not be able to publish as many papers as some others. If you don’t publish as many papers as others, you will not be promoted for the positions that are already very rare in academia. The hiring process is often all about the CV building and numbers.

Are there any common misconceptions about your area of research?

Misconceptions in AI are very common and I am not sure if all of them can be addressed! This could probably be caused by computer scientists not being great at dissemination. We build great stuff, but we are usually shy to explain what it is that we built.

For instance, people often think that AI acts like the human brain – but in truth, AI is only a software that the developers are implementing. The systems are far from comprehending their surroundings the way humans do. They are not able to learn on their own and we still struggle to implement an AI that makes jokes or understands jokes!

What are some of the areas of research you’d like to see tackled in the years ahead?

There are plenty of AI applications these days that are well known to discriminate against certain races, genders, religious groups, age groups, etc. In future, I would love to see AI evolving in the direction of eliminating the bias and discrimination factors to the best extent possible.

Additionally, considering that many day-to-day applications rely on AI models, which may result in wrong predictions, there should be more focus on explaining to the end users the reasons behind decisions taken by AI systems.

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Self-driving cars, which people can use to travel without needing to control the vehicle in certain parts of the journey, have seen advancements in leaps and bounds in recent years. Now, draft legislation in the UK is a sign of governments catching up to make the most of the technology.

According to the new rules, drivers in the UK can sit back and relinquish control when the self-driving function is turned on in cars that meet stringent criteria to qualify as self-driving. The rules point out that self-driving vehicles differ from vehicles that are fitted only with assisted driving features such as cruise control and lane assist.

When using a full self-driving mode, the new legislation will allow drivers to divert their attention from driving to forms of entertainment such as watching films and television on built-in screens in the vehicle.

Using handheld mobile devices, however, will remain illegal as drivers need to be ready at all times to take back control when needed.

“If a self-driving vehicle needs to hand control back to the driver, it will give you enough warning to do this safely. You must always be able and ready to take control, and do it when the vehicle prompts you,” the government specified.

Other commonplace road rules, such as a prohibition on drink driving or driving under the influence of drugs, will still apply. Drivers must also always be alert and awake when the car is in self-driving mode.

Mike Hawes, chief executive of the Society of Motor Manufacturers and Traders in the UK, said that qualifying technology could be available in the UK later this year, helping clear traffic congestion and making roads safer and more environmentally friendly.

“With the right regulations in place, consumers are set to benefit from safer, more efficient journeys while the UK will strengthen its position as a global leader in the deployment of self-driving technology,” he said in a statement published on the UK government website.

In February, Jaguar Land Rover announced that it was teaming up with Nvidia to bring autonomous tech to its cars starting 2025. Other big players, such as Tesla, Mercedes, Intel’s Mobileye and even Apple, have been making inroads in the self-driving space.

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The latest technology developments in low power wide area networks (LPWAN) are opening up the ability to monitor all kinds of equipment in remote areas. This technology now provides low-power links direct to satellite that can be combined with existing networks and cloud services. This is a powerful combination for both monitoring infrastructure and also for providing data that enables that infrastructure to be more efficient by reducing waste and making the best use of resources.

LPWAN offers the most power-efficient technology for environmental monitoring and is already widely used in the unlicensed 868MHz frequency band in Europe or 912MHz in North America.

The physics of these sub-GHz bands give significantly longer range than the bands at 2.4GHz used for Wi-Fi and Bluetooth, but with the trade-off of lower data rates.

For monitoring, however, this lower data rate is less of an issue compared to the benefits of the longer battery life that comes from the lower power consumption or, in some cases, the ability to remove the battery entirely.

Water monitoring solutions for irrigation schemes are now using solar panels to provide power for the sensor nodes across hundreds of square kilometres of desert. This removes the need for someone to go out and manually change the batteries.

Moreover, using the data sent to cloud and artificial intelligence (AI) systems for automated management and optimisation helps to boost crop yields without having to increase the use of fertilisers.

Other LPWAN sensors are using AI in forests to look out for wildfires. The incidence of wildfires is growing, destroying thousands of hectares of forest every year. Sensors on trees can detect levels of carbon dioxide and oxygen in the air and monitor the temperature, giving early warning of the conditions where wildfires are prone to occur. This gives first responders more time to organise prevention, or an effective defence.

However, these sensors still need to connect to a gateway, which for sub-GHz networks provides the link to a cable or cellular network. The latest enhancements to LPWAN protocols now allow sensors on the ground to connect directly to satellites in low Earth orbit.

The LoRa Alliance now has five satellite operators and network partners working to connect LPWAN sensors without the need for gateways on the ground.

The new capabilities that make a signal more robust to reach a satellite can also enhance the efficiency of smart cities. The new protocol gives smart meters greater reach and enables cheaper, lower-power monitors to refine the use of electricity and water, reducing leaks, and minimising waste. Sensors can be placed in many more locations without the worry or expense of having to replace the batteries.

Household leaks waste nearly 900bn gallons of water a year according to the Environmental Protection Agency in the US, and integrating LPWAN into water management systems and smart meters can identify areas where problems need to be fixed, helping to reduce water waste.

Other enhancements are also boosting the use of LPWAN networks in smart city and supply chain applications.

The 2.4GHz band is popular across smart cities as it is an unlicensed band available anywhere in the world. However, that band is full of different networks, which can create interference. Wi-Fi, Bluetooth, Matter, Zigbee, Thread and proprietary systems are all present for different applications.

Having an LPWAN system that is more robust in the 2.4GHz band means that sensors using that band can be used anywhere in the world, linking to any number of gateways. This also helps significantly reduce power consumption. Many protocols use a collision detection and retry architecture, and crowded bands mean more retransmission and higher power use. Using the more rugged LoRaWAN standard helps to keep power use low and extend battery life.

This can be particularly helpful across the supply chain. A low-cost way of knowing where containers are throughout the process of shipping, or where vehicles or equipment are located, is just the first step. This data can be ingested into databases and machine learning can then identify more ways to optimise the supply chain to make it more efficient. This increased efficiency across the globe can make a massive difference to help reduce the use of resources.

For example, Ercogener in France has developed an end-to-end asset tracking solution utilising Semtech’s LoRa devices and the LoRaWAN LPWAN standard that is used by the national state-owned railway company to track shipments across its rail network.

Elsewhere in France, JRI uses LPWAN sensors linked to the cloud to monitor the temperature of refrigerated containers for supermarkets, whether in situ or in transit. This both improves the efficiency of the transportation system but also ensures that the temperature of shipments are tracked and monitored. This can highlight problems before they become critical and prevent perishable shipments going to waste.

Optimising resources is vital for the future of our planet. The combination of global LPWAN devices and cloud services, including AI and machine learning on the data, are actively improving the way we use and conserve increasingly scarce resources.

By Alistair Fulton

Alistair Fulton is senior vice-president and general manager of the wireless and sensing products group at Semtech is the developer of LoRa, a long-range networking used by millions of internet of things devices worldwide.

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