Climate change poses a significant threat to the global environment. Since 1880, our planet’s temperature has risen by an average of 0.14° Fahrenheit (0.08° Celsius) per decade. More recently, global warming has doubled to 0.32° F (0.18° C) every decade since 1981. Surprisingly, according to NOAA’s temperature data, 2022 was the sixth-warmest year on record. Additionally, it’s worth noting that the ten warmest years have all occurred since 2010.

The future warming of our planet largely depends on the amount of carbon dioxide and other greenhouse gases we emit in the coming decades.

However, amidst these disheartening statistics, there is some hope. Brands and businesses from various industries are actively taking steps towards a greener future—a future that aims for carbon neutrality. They are harnessing the power of artificial intelligence and machine learning tools to reduce their carbon footprints and overall environmental impact.

AI has played a pivotal role in tackling climate change and striving for carbon neutrality. It’s fascinating how predictive analysis in logistics and deforestation monitoring, along with AI-powered recommendations for sustainable alternatives and the development of low-carbon materials, have made a significant impact.

Let’s be real here—AI isn’t a magical solution that can instantly reverse the effects of climate change. However, it unquestionably holds a crucial position in our battle against this global challenge. Its contributions are invaluable, and it continues to be a vital tool in our fight for a more sustainable future.

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Let’s take a look at the most basic and common ways in which AI is effectively (albeit slowly) controlling the effects of global warming.

AI’s Role in Carbon Neutrality

AI is stepping up as a valuable ally for climate leaders and businesses worldwide in the battle against global warming. It’s not just lending a hand in one way—it’s doing so in multiple ways! One of its superpowers lies in its ability to gather, analyze, and make sense of colossal and complex datasets on emissions and climate impacts. This incredible capability is empowering stakeholders to adopt a more structured and data-driven approach to pave the way for a greener future.

With AI in the loop, we can access vast treasure troves of data on emissions, climate change effects, and future projections.

In other words, AI is like our trusty sidekick, equipping us with the tools we need to make smarter choices and build a more sustainable world. It’s an exciting time, my friends!

Better Electrical System

The electrical system is filled to the brim with data, but not much has been done with the information in the last few years. Enter AI and machine learning, now suppliers can keep a check on electricity generation, and demand through AI forecasting. This way, the suppliers can explore ways to integrate renewable resources more effectively into national grids and bring down the waste generated. This process is underway at Google’s UK research facility DeepMind, which is leveraging AI to predict wind farms’ energy output.

Agricultural Emissions and Deforestation Surveillance

If you thought only engines and power plants were primarily responsible for greenhouse gas emissions, here’s an eye-opener. Destruction of trees and other plant life that have accumulated carbon mainly due to the photosynthesis process also contributes to greenhouse gas emissions. Unsustainable agriculture and deforestation release carbon back into the atmosphere. With the help of satellite imagery and AI, we can get to know the location where all this is happening and protect it.

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Predictions of Extreme Weather

AI has an immense capacity to detect major weather events like a shift in ice sheet dynamics and cloud cover. Scientists, with the help of AI, can assist in predicting extreme natural conditions like droughts and hurricanes. These forecasts can enable governments to deal with the effects of natural calamities more efficiently.

Creating Materials with Low-Carbon Content

Steel and concrete production are the greatest producers of greenhouse gas emissions. In this case, machine learning can help to reduce the number of emissions by creating sustainable alternatives. AI enables scientists to simulate the characteristics and interactions of previously undiscovered chemical compounds, which aids in the discovery of novel materials.

Efficient Transportation

Did you know that a quarter of global energy-related CO2 emissions is associated with the transportation sector and road users are responsible for two-thirds of this amount? Machine learning can improve efficiency by:

• Decreasing the number of unnecessary trips.
• Improving vehicle performance.
• Switching to low-carbon solutions like rail.

Shared autonomous vehicles with a reduction of car usage could be a viable solution in the near future, although no concrete evidence supports this.

Reduction in Waste Energy

About another quarter of energy-related CO2 emissions on a global level come from the energy consumed in buildings. It’s proven that buildings are seldom updated with newer technologies and innovations.

While a single building’s energy consumption can be reduced by 20% with the use of a few smart sensors that monitor the temperature of the air, water, and electricity, large-scale projects are likely to have a greater impact.

Tools for every individual to reduce carbon emissions.

It is a common misunderstanding that individual people are incapable of taking serious steps on climate change. And, citizens are required to have an understanding of how they can contribute. Calculating a person’s carbon footprint and highlighting small adjustments they might implement to lessen it using machine learning could be helpful.

• Opting for public transport or carpooling while traveling to work.
• Reducing meat consumption.
• Consciously reducing the use of electricity like switching off the fans and lights when not in use.
• Abstaining from using plastic.

Challenges of Carbon Neutrality with AI

A survey conducted by Boston Consulting Group (BCG) revealed that 87% of business executives agree that AI may be an effective weapon in the battle against global warming. These leaders claim that 43% of their companies can see adopting AI to aid in achieving their environmental objectives. Yet, to achieve holistic results, AI and individuals, communities, and organizations need to work together and fight the challenges and roadblocks.

Recommended: Industries that are Benefiting from Carbon Neutrality Using AI

User-friendliness

Whether AI solutions are created for companies, governments, or consumers in general, user-friendliness is essential if they are to be adopted widely. They must be easily available, give the user with real benefits, and present precise details which will help the user make decisions.

For instance, in some places, measuring emissions and monitoring natural carbon sinks with the help of AI tools is a little difficult. The basic reason being the majority of currently available AI-related environmental alternatives is dispersed, challenging to reach, and underfunded. In fact, even when it comes to public- and private sectors, 77% of the leaders are of the opinion that the lack of AI solutions is a big issue, while 67% blame a lack of faith in AI-related data and analysis, and 78% claim that a lack of AI experience is a glaring barrier to their organization’s efforts to apply AI to address climate change.

The Quest for the Right Resources

To reap the maximum benefits of artificial intelligence and its promise to tackle environmental issues and global warming, one needs the right kind of resources and the appropriate network to support the initiative. To optimize AI’s efforts, we need financial protection through the correct resources, decision-makers, and skilled professionals. While financial support can help to bridge the gap between deploying AI and academic research, effective networking involving leaders and policymakers can establish awareness and encourage adoption. Discussing and sharing knowledge on ethical practices and potential applications can further ensure that technologies are ready for wider government and commercial adoption.

Enhancing Knowledge & Strengthening Skills

Capacity building is a very crucial part of leveraging AI for carbon neutrality. It can be defined as the process of enhancing the knowledge, talents, procedures, and assets that enable communities and groups to endure, adjust, and prosper in a world that is undergoing rapid change. Civil employees, business executives, and various other stakeholders can be properly trained and re-skilled to utilize and understand AI solutions in the most crucial situations. Additionally, given that many nations will be differentially impacted by environmental shifts, current AI studies require being more inclusive.

The Trust Factor

AI is dynamic, complex, and promising, yet, in the end, it often boils down to one common point – the risk of ethical behavior, be it intentional or unintentional. And so, it is of utmost importance that industry leaders gain the trust of environmental leaders and visionaries and properly leverage AI. They must ensure the use of detailed and trustworthy supporting datasets, and prioritize interpretable and understandable results.

Final Thoughts

Global temperatures are rising, droughts are getting worse, and storms are getting more intense, all signs that the changing climate has begun to have a significant influence on the environment, society, and economy. Every region of the world is being affected by significant changes in physical threats, be it sea level rise or wildfires. Needless to say, artificial intelligence algorithms and machine learning analytics can assist businesses, cities, and people in many different ways to combat the battle against global warming. Artificial intelligence-powered gadgets that lower emissions are still being developed and designed by businesses.

Despite the advancements in technologies backed by cutting-edge research, there are still many obstacles in the way of AI deployment to assist emerging solutions overcome them and reach their full potential at scale. Irrespective of their formal involvement in AI or ecological issues, all individuals, groups, and entities have an essential part to play. To sum it up, the sooner we reduce greenhouse gas emissions, the lesser risks and impacts we have to deal with in the coming years.

The support that AI solutions currently receive is far from enough; they require access to funding, knowledgeable decision-makers, and skilled practitioners.

The post Combating Climate Crisis: The Challenges Of Carbon Neutrality With AI appeared first on AiThority.

In the past, ad systems relied on basic heuristics, which can be effective for making immediate judgments, but often result in inaccurate conclusions. To really optimize for what advertisers and marketers care about — which is delivering custom marketing campaigns on the open internet that result in a hard ROI on their ad dollars — you need first-party data and a sophisticated machine learning (ML) platform that can optimize for return on ad spend (ROAS). Under the cover of a modern ML-based platform, there are many different ML models doing everything from predicting conversion likelihood to determining the best price to bid for an individual ad request.

AI ML in Marketing: AI and Big Data Analysis Used to Find Brands’ Emotional Connection

Activating your first-party data is more important than ever given the seismic privacy changes happening in the industry, including Apple’s ATT and Google’s Privacy Sandbox, which are making it incredibly challenging for traditional ad tech systems to adapt. ML-based approaches, however, have a distinct, almost magical ability to adapt to these changes faster and more holistically than what a vigilant technical team can do.

Developing first-party data sets isn’t as easy as it sounds, however. Marketers need to be wary of the quality of the data that goes into machine learning models. These models have the capability to drive accurate and effective results; however, it can have an equal and opposite effect if brands are relying on static third-party data. To mitigate this, businesses need to invest in building and growing first-party datasets that ensure ads are being targeted more precisely and accurately to a relevant audience.

Keys to Developing Quality First-party Datasets

In performance marketing, it’s critical to have confidence in the quality of data being used.

There is a famous saying in the machine learning world – garbage in, garbage out. Marketers should be reassured that there is no fraudulent data in their system and have the ability to remove such data – ensuring the model is being fed with quality inputs. 

ML models make use of quality data that is a mix of contextual and behavioral signals that can help infer an individual’s intent or interest in a particular ad. In general, if that data can help increase engagement for an ad, it is useful.

There are many types of useful data, and quality is largely determined by accuracy — for example exact location versus an inferred metro area; consistency, which requires having the same data available for every user or ad request; and timeliness, which relates to how often the data is refreshed.

Building and Growing First-Party Datasets

The imminent depreciation of third-party cookies and improved privacy for device IDs mean that marketers and advertisers will be challenged to target consumers in a meaningful way. The good news is they have access to first-party data, which can be turned into gold if harnessed and used correctly. 

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First off, it is important to understand what constitutes personally identifiable information (PII) in context of individual users. There are both intuitive and non-obvious ways that data can be PII, so it really requires a lot of thought and an overall strategy. Keep in mind that PII is not just how your product/service uses a piece of customer data, but the downstream potential for it to be combined with other data to identify individuals.

Building a strong first-party dataset starts with having a system for collecting the data around your user journey and engagement activities in your products or services, including how customers shop, the brands they prefer to purchase, their site journey, pages visited, items clicked and navigation sequence, and organizing it into user profiles, segments, and audiences. Like what product managers need to build great products, marketers need to have a thorough understanding of their users, the user journey, and, ultimately, the value users derive from a product or service.

The next step is to integrate the data with other business systems (CRM or data warehouse) so you can gather insights through a mix of analytics, Mobile Measurement Partner (MMP), or business intelligence tools.

With the proliferation of cloud data warehouses, this doesn’t have to be a massive initial effort since these platforms can scale to manage more complex use cases as your data grows.

Unlock the Power of Your Data Through Sophisticated Machine Learning

In the past, marketers had to rely on human intelligence and manual optimization such as daily budget adjustments or pub throttling. With the advent of machine learning, those tactics no longer add value and quite often actually have a negative impact. It is extremely important to “let the machines do the work” and minimize any extraneous human interaction or data throttling.

In addition to human error, there are other factors contributing to the need for modern ML, including an explosion in the amount of data available, particularly as mobile device growth and usage are now at a peak; the sophistication in tools and systems for supporting large scale data processing in the cloud; and the sophistication in ML algorithms, particularly neural network-based ML.

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It’s important to note that not all machine learning systems are created equally. To successfully leverage the power of the technology and achieve performance marketing goals such as ROAS, CPI, CPA, or revenue, the ML platform should include the following:

• Sophisticated ML technology, including deep neural networks (DNN) to assess hundreds of features and their impact on downstream engagement/conversion (ROAS).
• Large-scale data processing, including the ability to listen to and process an incredible amount of data to continue informing and training the ML models.
• Highly performant output, meaning the system should make multiple predictions and optimize immediately, iteratively, and in real time, and continue learning.
• A combination of first-party data with proprietary user data, which allows the system to begin learning about users before launching an advertising campaign. 
• Deep-learning based ML and historical performance data – allows for quickly generalizing with very limited campaign responses. For example, by observing advertising responses for a limited geo, a modern ML platform can precisely predict how a campaign would perform on other geo locations. 

Another important aspect of machine learning is it allows marketers to develop privacy-safe approaches to doing relevant ad targeting, which is critical in today’s privacy-first environment.

Machine learning can be used to construct more advanced behavioral cohorts that make it impossible to accidentally reveal PII information. ML models for targeting can also be run “on the edge“ so that sensitive information never leaves a user’s mobile device.

This is an exciting and innovative time for the industry. Advanced ML-based solutions are enabling advertisers of all sizes to develop privacy-safe or privacy-first approaches that deliver relevant ads, generate ROI, and accelerate their business.

[To share your insights with us, please write to sghosh@martechseries.com]

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New Delhi flirted with its all-time highest April temperature on Thursday as people and animals tried to cope with the abnormally intense and prolonged heat wave

While parts of the eastern United States are dealing with lower-than-normal temperatures, thousands of miles away, India is baking under a new round of heat, and residents of the Indian subcontinent can expect the brutally warm air to linger.

It isn’t unusual for parts of India and Pakistan to have some cities among the top 10 hottest places in the world, but what is unusual is how they are completely dominating the list. Looking at 24-hour daily highs, all 10 of the hottest locations were found in India and Pakistan, and the hottest temperature recorded on Earth at official weather stations Thursday was a toasty 116.6 degrees Fahrenheit (47 Celsius) in Jacobabad, Pakistan.

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With temperatures consistently 5 to 10 F above normal this April in Indian cities like New Delhi, home to more than 30 million people, some Indians are blaming climate change for the scorching temperatures.

On Thursday, New Delhi nearly ranked among the world’s top 10 when it topped out at 109 degrees (43 C), about 5 degrees shy of the all-time record high temperature for April there, which is 114.1 F (45.6 C) measured on April 30, 2019, according to AccuWeather Senior Meteorologist and Lead International Forecaster Jason Nicholls. The city matched the 109-degree F mark again on Friday, while Banda, India hit 117.3 F (47.4 C).

In contrast, Death Valley, California, famous for its reputation as one of the hottest places on Earth, hit a high temperature of 99 on Wednesday.

“We are getting a return gift from nature in the form of heat. Us humans have worsened our environment. Owing to our increased use of air-conditioners and cars, I feel that the heat will keep rising,” Parul Bakshi, a resident of Chennai, India, told Reuters. “We will see the climate changing rapidly. This is also why I think that it is this hot.”

NASA noted that 10 major cities were exposed to high temperatures above 110.8 F (43.8 C) on Wednesday.

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Meteorologists from the India Meteorological Department (IMD) found that March 2022 was the hottest March for India as a whole since 1901, with average highs jumping to a staggering 3.35 degrees Fahrenheit (1.86 degrees Celsius) above the climatological average. A scientist on Twitter noted that the last six weeks in New Delhi have averaged more than 7.5 F (4 C) above normal, matching the worst heat wave on record from 2010.

Unfortunately for animals and people in India, AccuWeather forecasters are not expecting much relief from the heat anytime soon, perhaps not until the monsoon season begins in June.

“A brief change in the weather pattern can bring some relief around next Tuesday or next Wednesday,” said Nicholls. “Any relief looks to be brief as heat is expected to return for the first full weekend of May.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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AccuWeather NOW, the new video streaming product from AccuWeather, the proven leader in weather forecast accuracy, announced it has officially launched on Amazon Freevee, a free ad-supported streaming service that delivers premium content without having to purchase a subscription.

Amazon Freevee viewers will now have to access AccuWeather’s forecasts as well as 24/7, continuous daily programming, dedicated to all things weather, including extreme and natural events, global forecasts, climate and weather-related news impacting our changing world and long-and short-form documentaries through the streaming platform, accessible and free to watch and stream from any device.  Amazon Freevee is free, customizable and includes critical weather information from AccuWeather NOW^TM streaming service into their platform listing.

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The AccuWeather NOW^TM streaming service features dramatic weather video; stories illuminating the potential impact of forecasted weather on sports, health, travel and other everyday activities; engaging social weather content from popular platforms such as TikTok, Instagram, Twitter, and others; as well as long-form storytelling of major weather events and environmental wonders around the world.

“We are delighted to bring AccuWeather NOW to Amazon Freevee’s growing user base and footprint, delivering high-quality streaming content as audiences’ appetites grow for weather and climate news, that is free and easy to find,” AccuWeather Vice President, Content, Trish Mikita of the AccuWeather Network, which offers the AccuWeather NOW^TM streaming service.

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AccuWeather NOW^TM steaming service complements AccuWeather’s existing suite of platforms, including its award-winning 24/7 national AccuWeather Network, which already reaches 36 million households with another 1.5 billion people globally accessing AccuWeather forecasts via digital devices, such as desktop and apps, as well as radio, television and newspapers and digital out of home.

Freevee is available as an app on Fire TV, Fire Tablets, and as a free Channel within Prime Video, across hundreds of devices. IMDb TV is also available as an app on third party devices including Roku, Samsung smart TVs (2017-2021 models), Comcast’s Xfinity Flex, Xfinity X1, Chromecast with Google TV, NVIDIA SHIELD and other Android TV devices, Xbox One, Xbox Series X|S, PlayStation 4 and PlayStation 5 consoles, as well as LG Smart TVs (2018-2021 models). The app is also available on iPhone, iPad and Android mobile devices.

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[To share your insights with us, please write to sghosh@martechseries.com]

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Xactly provides Japanese market with the service and solutions to drive predictable and profitable growth

Xactly, the leader in intelligent revenue solutions, announced its further expansion into the Asia-Pacific (APAC) region with the upcoming launch of Xactly Forecasting in Japan. The company’s entry into Japan builds on the company’s sales momentum and 71% year on year growth.

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Xactly will continue to work closely with Salesforce to increase adoption within Japan and across APAC, continuing the companies’ 16-year partnership. Xactly will leverage its Salesforce integrations to reach new customers and support businesses with the unmatched capabilities of its Intelligent Revenue platform and forecasting solutions.

“We have long considered expansion into Japan, and we’re excited by the current opportunity to support growing enterprises in the region. Japan is the fourth largest market in the world, and continues to advance at a rapid pace,” said Chris Cabrera, founder and CEO of Xactly. “As organizations face uncertain market conditions, many are looking to build business resilience through a more intelligent approach to forecasting revenue growth.”

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“We are pleased to be a part of Xactly’s expansion into the Japanese market through this strategic alliance,” said Yasutaka Fukuda, Board Member of Xactly Japan.”We believe that Xactly’s Intelligent Revenue Platform, which has been adopted by many global companies as an industry leader for the past 16 years, is a predictable and profitable business solution that is essential for Japanese companies to achieve mid- to long-term growth. ”

Looking ahead, the company has its sights set on servicing the evolving Incentive Compensation Management (ICM) segment in Japan, which is an emerging priority among local organizations looking to boost sales team performance. Xactly Incent will meet these revenue intelligence and compensation planning needs across the country and broader region.

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[To share your insights with us, please write to sghosh@martechseries.com]

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Supply chains are the systems of organizations, people, activities, information, and resources involved in supplying a product or service to a consumer. The proliferation of AI-based video solutions has impacted supply chains in industries all across the globe. Analysts have reported consistent growth in this space, with no end in sight, projecting revenues upwards of $8 billion through 2026. As technology continues to advance, it’s important to understand the impact it already has on supply chain management practices, as well as the ways that it can continue to reshape the global industry. 

Top 10 Countries and Cities by Number of CCTV Cameras

AI-based Video Solutions Ensure Driver and Road Safety 

AI-enabled advanced driver-assistance systems (ADAS), driver monitoring systems (DMS), and cabin monitoring systems have become critical in today’s fleet management practices. AI-based video telematics can assist ADAS with automatic warnings, both to the driver or the fleet manager for incidents such as collisions, lane departure, and object/pedestrian hazard warnings. In addition, AI camera applications in the cabin along with driver monitoring systems can improve cabin and driver safety, generate alerts for drowsy/distracted drivers, reduce insurance costs, and ultimately help resolve vehicle-involved incidents in a more timely fashion. 

While in transit, the use of AI-enabled analytics makes it possible for fleet managers to analyze truck utilization patterns and get a view of loading/unloading activity. This information allows supply chain managers to better understand the overall productivity of their fleet and make changes whenever necessary. Additional capabilities like facial recognition and driver wellness can be more efficiently monitored to ensure greater control and optimization throughout the supply chain.

AI-based Video Solutions for Workplace Compliance 

AI-based cameras can also help keep workers safe. During 2020, supply chains had to quickly adapt to myriads of changes caused by the COVID-19 pandemic, further emphasizing the need for safe workplace practices. AI models embedded in CCTV cameras can monitor social distancing practices and provide mass fever detection in warehouses and other workplaces. Real-time fever detection can reduce work stoppages and delays and improve employee safety and trust—creating several competitive advantages. AI can also detect and prevent other workplace hazards and take real-time action, like instant corrective warnings to significantly improve safety and reduce accidents. 

Inventory Management with AI-based Video Solutions

AI-embedded closed-circuit television (CCTV) cameras offer increased visibility and control for a fully connected supply chain. These enhanced cameras automatically gather data in real-time through live video feeds. The AI-based systems then add decision-making capabilities to these devices, which are then able to analyze data, recognize critical and/or abnormal events, and send automated alerts. These crucial insights minimize risk and help to avoid undesirable scenarios, leading to better outcomes and more efficient management of supply chains.

AI-enabled cameras and video analytics are driving efficiencies across inventory management, as CCTV cameras backed with AI video analytics can instantly track and detect any kind of suspicious activity and send alerts in real-time. 

Looking to the Future 

Evolving technologies aim to constantly improve and streamline supply chain management,allowing organizations to increase efficiency without the need for additional resources. Accelerated by the pandemic, AI is being infused into many aspects of the supply chain to meet the increased demand of e-commerce and last-mile deliveries for customers world-wide. From autonomous forecasting and planning to customer communication management, AI will be capable of optimizing the data each organization collects to effectively improve the supply chain from end-to-end. 
[To share your insights with us, please write to sghosh@martechseries.com]

The post How AI-based Video Solutions are Creating Smarter Supply Chains appeared first on AiThority.

RateGain Technologies announced at the 2021 International Car Rental Show the launch of revAI, the first end-to-end AI-powered demand forecasting and price optimization platform for car rentals to make every forecast profitable.

The summer of 2021 witnessed a surge in car rental demand, with most travelers experiencing supply shortages, highlighting the problematic process of forecasting demand accurately and managing fleets more precisely. This supply-demand gap limits revenue maximization opportunities for car rental operators.

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revAI solves revenue leakage by leveraging 25 demand indicators that drive hyper-local demand at a city level to help car rental operators clearly understand the market potential and adjust their strategy to reach their maximum revenue potential in any given day. However, unlike most demand forecasting solutions, revAI goes a step further and combines a price optimization module, which enables revenue managers to capture the incremental market share through an AI-driven-price recommendation engine.

While most demand forecasting solutions rely on historical bookings, revAI is one of the first platforms to leverage forward-looking demand indicators that are more credible in quantifying demand at a hyper-local level for the city. The forecast and understanding of market demand can also help identify dates that need attention, ensuring that car rental operators never lose an opportunity to maximize.

The platform drives automation and digitization. It is aimed to help revenue managers eliminate manual processes such as complex spreadsheets and multiple data sources. revAI provides revenue managers with one single platform to understand demand, determine their pricing strategy and let the system execute that strategy seamlessly to stay ahead and drive recovery through sophisticated machine learning and artificial intelligence framework.

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Commenting on the launch, Harmeet Singh, Group CEO, RateGain, said, “Car rentals are one of the hardest hit by demand volatility and have very little bandwidth or technology support to adapt. With revAI, we are committed to changing that. Our solution will essentially bridge the gap between forecast and revenue maximization by ensuring that every rental is profitable, reduces time, effort and improves margins.”

revAI is integrated with leading industry partners allowing independent operators and franchisees to start realizing the benefits and learn how your team can leverage and bring technology-powered transformation to your car rental revenue management and pricing strategy in the post COVID era.

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• Industrial Software Leader Joins International Coalition to Restrict Global Warming to 1.5°C  As Part of Sustained Commitment to Climate Action

AVEVA, a global leader in industrial software, driving digital transformation and sustainability, announced that it has committed to setting 1.5°C-aligned emission reduction targets across all three Scopes as part of joining the  Business Ambition for 1.5°C campaign. The announcement was made during a meeting at AVEVA’s London office attended by Kwasi Kwarteng, UK Secretary of State for Business, Energy & Industrial Strategy. The move affirms AVEVA’s commitment to set both short and long-term targets that are in line with the most ambitious aims of the Paris Climate Agreement and reflects a science-based approach to climate action.

“As outlined by the global scientific community in last week’s Intergovernmental Panel on Climate Change report, the window we have to take action on climate is closing fast,” said Peter Herweck, AVEVA CEO, at the meeting. “We have joined Business Ambition for 1.5°C because we are deeply committed to being part of the solution to the climate crisis, both through the industrial software that we make to support our customers on their digital journey and in the daily actions that we take to run our own business. By working together with our customers, partners, and other key stakeholders such as the UK Government, we believe we can create an inclusive net-zero economy in line with the 1.5°C pathway.”

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Business and Energy Secretary Kwasi Kwarteng commented, “It’s great to see companies like AVEVA committing to tackling climate change and joining the Race to Zero and the Business Ambition 1.5°C campaign. As a country, eliminating our contribution to climate change by 2050 simply will not be possible without business playing its part and I urge other companies to follow suit and sign up without delay.

“Advanced technologies have a major role to play in cutting emissions, while at the same time boosting investment and creating new green jobs. It was fantastic to see first-hand how AVEVA is supporting its many customers across the world to transition to a clean, green way of doing business and to seize the myriad opportunities that this brings.” Secretary of State Kwarteng said.

Business Ambition for 1.5°C is a global alliance led by the Science-Based Targets initiative (SBTi) in partnership with the UN Global Compact and the We Mean Business coalition. It aims to prevent the worst impacts of climate change and avoid irreversible damage to our societies, economies, and the natural world by limiting global temperature increases to 1.5°C above pre-industrial levels. Reaching that goal requires halving greenhouse gas emissions by 2030 and hitting net-zero emissions by 2050 worldwide. Over 600 companies representing more than $13 trillion in market capitalization have signed up to the Business Ambition for 1.5°C initiative so far. It is widely recognized as the gold standard for corporate climate action.

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“Achieving the targets will not be easy,” added Herweck. “However, we are confident that through a smart combination of implementing energy reduction measures across our offices, procuring renewable energy, and engaging with our suppliers and customers on climate action, we can greatly reduce our overall emissions with minimal reliance on carbon removals. The majority of our UK facilities, including London, Cambridge, Chesterfield and Manchester, are running on clean power and we are actively working to increase our renewable energy sourcing globally.” In the US, AVEVA’s California facilities, in Lake Forest, San Leandro and Carlsbad, have already switched to a green tariff.

Beyond making changes to accelerate AVEVA’s own use of renewable energy, the company’s software solutions enable many customers across the world to decarbonize and speed up the transition to a net-zero emissions economy. By enabling energy savings, emissions monitoring and mitigation, materials efficiency, waste reduction and supply chain optimization, AVEVA solutions support more sustainable industries.

AVEVA already contributes to a number of corporate sustainability initiatives that bring together companies to help tackle climate challenges collectively, including BSR, the UN Global Compact, and the Renewable Energy Buyers Alliance (REBA). In signing on to the Business Ambition for 1.5°C commitment, AVEVA is also pleased to be joining the UNFCCC Race to Zero.

This latest climate pledge is aligned to AVEVA’s goal of showing that a 1.5°C-compliant business model is possible ahead of COP26 in November when governments and industries will strengthen their contributions to the Paris Agreement and to tackling global warming. It also reflects AVEVA’s culture of collaboration and its commitment to working with stakeholders across the value chain to help safeguard the planet for coming generations while advancing the net-zero industries of the future.

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Branch Energy – a tech-powered, green energy provider focused on helping consumers reduce their energy bills and carbon footprints – has raised $4.5 million in its seed round. This round of financing was led by Comcast Ventures with participation from Global Founders Capital, Inovia Capital, and Assaf Wand – CEO of home insurance unicorn Hippo.

Branch Energy was co-founded by Alex Ince-Cushman, ex-Palantir and former nuclear fusion researcher; Daniel MacDonald, a serial B2C entrepreneur; and Todd Burgess, an energy industry veteran. The trio will use the funds to expand the team, and support the data and analytic infrastructure development at the heart of the company’s approach.

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Electricity production is one of the biggest sources of greenhouse gas emissions worldwide and accounts for 25% of US emissions. Transitioning the electricity grid to green energy is therefore critical to reducing the effects of climate change. Recent catastrophes like the black outs in Texas and the fires in California highlight that the current energy system is struggling to cope with climate-related change. Branch Energy is setting out to help by showing consumers that green energy can actually save them money, time and hassle — and by providing a dramatically better customer experience than incumbent energy providers.

“Climate change is a staggeringly large challenge and we’re building Branch Energy, from the ground up to be part of the solution. In particular, we think we can have the biggest impact by focusing on opportunities that reduce our customer’s energy bills and also help decarbonize society. Fortunately, this intersection is actually much, much larger than most people appreciate,” says Alex Ince-Cushman, Branch Energy’s CEO and cofounder.

Branch Energy will initially launch in the US in states with deregulated energy markets (where consumers are able to choose their energy provider). In these markets, Branch Energy will offer customers 100% green energy, be their interface for billing, payment and customer service while also helping them install and finance smart energy devices. Branch Energy is aiming to sign up its first customers in Texas this fall.

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Despite the considerable energy-saving benefits of modern devices such as smart thermostats, smart water heaters, solar arrays, etc, the installation rate for these devices remains persistently low in the US. These low deployment rates are in large part due to the hurdles the average residential customer faces in getting devices installed. “Most people don’t wake up on a Sunday morning to do complex economic calculations on the payback period of a smart water heater, then go buy the device with cash, then coordinate with a plumber to install it, to eventually get savings in the future. It’s just too much friction for most people,” says Daniel MacDonald, cofounder and Branch Energy President.

In addition to delivering 100% green energy to its customers at a great price, Branch Energy will help customers save even more by doing the heavy lifting of device installation. By combining energy usage data, satellite imagery, hyper-local weather forecasts, AI and more, Branch Energy will calculate the economic benefit of each of these devices for each customer, and then coordinate financing and installations. The combination of energy saving smart devices and delivering 100% green power will make Branch Energy a compelling option for customers both financially and environmentally.

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