In a world overshadowed by the rapid deterioration of its climate, AI engineers are beginning to apply machine learning technology to issues of environmental justice and crisis. In California, where wildfires have ravaged over 570,000 acres of land and forced 41,000 evacuations already this summer, AI is being used to prevent and monitor forest fires throughout the state.
When securing executive buy-in for your potential AI project, there are a number of considerations to keep in mind. It’s necessary to prepare a strong proposal that not only takes account the motivations of your leaders, but also makes a case for your project’s technical feasibility. In this article we dive into five tips to consider when attempting to secure executive buy-in:
The demand for data scientists has never been higher, and 86% of executives claimed that AI would be a “mainstream technology” at their companies in 2021. As Artificial Intelligence becomes more widely adopted in business practices, many companies are beginning to utilize AI Consultancies to optimize customer experience, reduce cost, and more. When starting a new AI initiative, working with an experienced consultant is the way to go. That’s why we curated this list of top 5 reasons you should hire an AI Consultant.
The increasing prevalence of AI education technologies raises questions and concerns about the role of AI in the classroom. We explore AI-powered chatbots, language assessments, grammar assistance, and homework help to show AI’s potential as a tool for increasing access to educational materials and automating tasks for educators, allowing them to focus on complex responsibilities and direct student interactions.
Hearing aids are a crucial assistive technology for the deaf and hard of hearing communities. However, many who would benefit from the use of hearing aids show a reluctance that stems from a lack of confidence in their value. AI is being used to address the concerns of users with the goal of improving accessibility as well as mental health and cognitive outcomes.
AI has the potential to help create a more equitable, efficient, and innovative educational system. Artificial Intelligence is currently reshaping the way students learn in classrooms all around the world. We address six ways that AI can be leveraged to enhance the ever changing educational landscape for students and teachers alike.
Since the first oil well was dug in 1859, we have been extracting carbon from the ground and pumping it into our atmosphere. Similar to the hundreds of thousands of oil wells around the world, what if we had many CCS systems capturing carbon, often in the form of oil, and injecting it back into the ground?
There is strong demand from governments, environmentalists, and citizens alike to keep our oceans clean and preserve the biodiversity and critical services they provide to life on Earth. Many emerging companies and organizations are changing the landscape of ocean conservation by developing innovative AI monitoring techniques and robotic technologies to identify pollution in our oceans and waterways and provide an expedited approach to cleaning it up.
Illegal logging is an environmental and economic loss for tropical regions like the Amazon. Illegal logging is associated with billions of dollars of lost revenue each year in addition to depressed timber prices, yet effective strategies to curb illegal deforestation are hard to find. Harnessing AI serves as a promising innovation for enhancing the accuracy of forest monitoring, with the potential to be adapted to the Amazon basin and other tropical regions.
In recent years, we’ve witnessed the shocking imagery of Australia, the western United States, Europe, and the Amazon rainforest engulfed in flames, the unprecedented intensity, duration, and extent of the fires inflicting irreversible damage on countries, economies, ecosystems, and the atmosphere. Managing and conserving forest resources remains a top priority, but mapping and monitoring global forests are crucial to understanding how to properly manage and protect them, especially in monitoring wildfires and illegal deforestation, as well as knowing which forests to prioritize preserving. Identifying and monitoring forests with strong conservation value and high carbon stock is also a huge leverage point for targeted intervention of Artificial Intelligence.
In this article, we explore some practical uses of AI driven automated text generation. We demonstrate how technologies like GPT-3 can be used to better your business applications by automatically generating training data which can be used to bootstrap your machine learning models. We also illustrate some example uses of language transformations like transforming english into legalese or spoken text into written.
In a world overshadowed by the rapid deterioration of its climate, AI engineers are beginning to apply machine learning technology to issues of environmental justice and crisis. In California, where wildfires have ravaged over 570,000 acres of land and forced 41,000 evacuations already this summer, AI is being used to prevent and monitor forest fires throughout the state.
The application of AI in creative spaces like music and art is not new, but recent years have seen a dramatic expanse in machine learning capabilities in music composition. AI is being used by researchers and startups to compose soundtracks and soundscapes, and to create original songs within the style of specific genres and artists. Just as work by writers regularly appears alongside robot authors in sports, financial, and other news, Human musical artists are increasingly sharing the stage with artificial intelligence.
Within this last year alone, there has been a paradigm shift in model development as research groups are ingesting (nearly) the entire world's worth of information on the internet to train massive deep learning models capable of performing fantastic or frightening feats, depending on your perspective. In this article, we explore an AI compositional technology, known as generative modeling, and demonstrate its ability to simulate human-realistic text.
As an AI Consultant, I get a front row seat to AI and innovation; I repeatedly see when it succeeds, and when it fails. I’ve been building AI and machine learning based systems for over 20 years, in many different companies, cultures, and problem domains. During this time, I’ve noticed a number of patterns that cause the deployment of AI systems and AI powered features to fail.
