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Easing the Expense Report Blues: Microsoft & Amex Tap AI for Smarter Solutions

Expense reports are a tedious and time-consuming task, but AI may change that. Microsoft and American Express have partnered to leverage Microsoft Cloud and AI technologies to improve expense report management. The solution, which is built in-house by Amex, will automate expense reporting and approvals by using machine learning and an AI-powered decision engine that understands the company’s travel and expense policy. The system will use an employee’s purchase and payment history to categorize and assign a risk score to individual transactions, which can then be automatically approved. Microsoft will be the first to test the solution and later integrate it with its own internal expense system. Although there is skepticism about the accuracy of AI-powered solutions, the technology is quickly advancing in the financial services and corporate travel industry.

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Flexible Intelligence: The Future of AI with Liquid Neural Networks

Researchers in artificial intelligence have made significant progress in creating neural networks that mimic the structure of the human brain. Traditional neural networks, on the other hand, lack the adaptability to new situations and circumstances. In 2020, MIT researchers introduced “liquid neural networks,” which were inspired by the roundworm Caenorhabditis elegans. These networks can run faster and more accurately than traditional continuous-time neural networks, and their underlying algorithms can be changed on the fly. A probabilistic process governs the strength of connections between artificial neurons in liquid networks, giving the networks built-in variability that makes them more adaptable. A liquid network was used to steer an autonomous car in an early test, and it was much more responsive than a conventional neural network. The development of liquid neural networks, which offer a more flexible and adaptable approach to machine learning, bodes well for the future of AI.

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The Power of AI in Personalized Learning: Revolutionizing Education

Andreessen Horowitz a16z looks at the introduction of AI technology such as ChatGPT that has sparked significant debate about its impact on various fields, particularly education. While some are concerned that it will lead to cheating and the replacement of human teachers, the truth is that if used correctly, AI has the potential to greatly improve students’ ability to think critically and expand their soft skills. Here are five predictions for the impact of artificial intelligence on education and learning:

  • With the help of AI, one-on-one support for services such as tutoring and therapy will become more accessible to a wider range of people.
  • With AI’s ability to adapt to students’ learning modalities, interests, and skill levels, personalized learning will become a reality.
  • The use of AI-powered virtual mentors and historical figures will help learners gain access to mentorship opportunities.
  • AI-augmented therapy will provide patients who are hesitant to seek help from a human therapist with more affordable and approachable options.
  • AI will revolutionize assessments and testing by accurately tracking knowledge and progress, as well as providing personalized feedback and content reformatting.

By investigating these predictions and applications, it is clear that AI has the potential to transform education and learning by making it more personalized, accessible, and engaging for all.

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The A.I. Wars Heat Up: Google’s $100 Billion Mistake with Bard Chatbot

The artificial intelligence market is becoming more competitive as tech companies strive to outperform one another with AI-powered products. The unveiling of Google’s upcoming AI chatbot, Bard, was marred by technical difficulties and an error in its first advertisement, resulting in a $100 billion loss in market value for Alphabet, Google’s parent company. With its fast-growing consumer app status and potential to disrupt internet searches, OpenAI’s ChatGPT, a human-like text generating chatbot, is ahead of the competition. Microsoft, Google, and Baidu are all rapidly developing their own AI products, with Google being the most advanced, having developed LaMDA, a language learning model similar to ChatGPT. Bard’s error, on the other hand, emphasizes the importance of a thorough testing process before broad release, as it joins other chatbots in providing inaccurate and biased responses.

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Unleash Your Inner Musical Genius: Audialab and AI

AI technology is rapidly changing the way music is produced. Audialab, an American company, is at the forefront of AI-assisted music production and is developing software that will change the game. Emergent Drums, their first plugin, is an AI-powered drum machine that doesn’t rely on pre-existing samples or synthesis engines. Instead, it generates drum samples using AI and machine learning technology. The plugin employs a neural network trained on tens of thousands of existing samples, studying patterns in the raw waveform data of these audio files to form its own representation of what different drum sounds could be.

Emergent Drums can generate countless variations on all of the traditional drum sounds, as well as toms and noise-based percussive sounds. The plugin is constantly learning and evolving, training itself with the sounds it generates. It should be noted that the plugin does not generate sounds using your computer’s hardware and can only be used online. While Emergent Drums is not a replacement for your sample library, it would be an excellent addition to it. It’s worth noting that the majority of the samples produced have a crunchy, digitally lo-fi sound that would work well in a glitch/IDM track. Overall, AI technology is changing the way music is produced, and Emergent Drums is just the beginning.

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Could Moon dust block global warming?

In a paper just published in the open-access journal PLOS Climate One, scientists at the Center for Astrophysics | Harvard & Smithsonian and the University of Utah suggest a radical way to deal with global warming. In computer simulations, they found that when launched precisely, Moon dust would follow a path between Earth and the Sun, effectively creating shade, at least for a while.

The Earth’s atmosphere traps more and more of the Sun’s energy, which steadily increases the Earth’s temperature. This new strategy could reverse this trend by intercepting a fraction of sunlight before it reaches our planet.

A cool moonshot

The paper describes the different properties of dust particles, quantities of dust, and the orbits that would be best suited for shading Earth. The results were welcome news, the team says, because much less energy is needed to launch dust from the Moon than from Earth. This is important because the amount of dust required for a solar shield is large, comparable to the output of a big mining operation here on Earth. 

But wait: What if it blocks enough sunlight to create a permanently cold, uninhabitable planet? Not to worry, advise the scientists. The Sun’s radiation naturally disperses the dust particles throughout the solar system, meaning the sunshield is temporary and particles do not fall onto Earth. 

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What if robots could collaborate with artists?

Carnegie Mellon University’s Robotics Institute is exploring that idea

Their FRIDA (Framework and Robotics Initiative for Developing Arts, named for Mexican painter Frida Kahlo), uses a robotic arm with a paintbrush taped to it and AI to collaborate with humans on works of art.

FRIDA’s first paintings (credit: Carnegie Mellon University/The Robotics Institute)

FRIDA is a robotic painting system, “but FRIDA is not an artist,” says Peter Schaldenbrand, a School of Computer Science Ph.D. student in the Robotics Institute, who is working with FRIDA and exploring AI and creativity. “Instead, FRIDA is a system that an artist could collaborate with. The artist can specify high-level goals for FRIDA and then FRIDA can execute them.” Artists can direct FRIDA by inputting a text description, submitting other works of art to inspire its style; or by uploading a photograph and asking Frida  to paint a representation of it.

An artist can direct FRIDA by inputting a text description, submitting other works of art to inspire its style, or uploading a photograph and asking it to paint a representation of it.

One of the biggest technical challenges in producing a physical image is reducing the simulation-to-real gap — the difference between what FRIDA composes in simulation and what it paints on the canvas. FRIDA uses an idea known as real2sim2real. The robot’s actual brush strokes are used to train the simulator to reflect and mimic the physical capabilities of the robot and painting materials.

Beyond DALL-E-2

The robot uses AI models similar to those powering tools like OpenAI’s ChatGPT and DALL-E 2, which generate text or an image, respectively, in response to a prompt. But instead, FRIDA simulates how it would paint an image with brush strokes and uses machine learning to evaluate its progress as it works.

DALL-E 2 uses large-vision language models to produce digital images. FRIDA takes that a step further and uses its embodied robotic system to produce physical paintings. One of the biggest technical challenges in producing a physical image is reducing the simulation-to-real gap, the difference between what FRIDA composes in simulation and what it paints on the canvas. So FRIDA uses an idea known as real2sim2real. The robot’s actual brush strokes are used to train the simulator to reflect and mimic the physical capabilities of the robot and painting materials.

The team is also experimenting with other inputs, including audio. They played ABBA’s “Dancing Queen” and asked FRIDA to paint it.

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Generative AI: The Next Consumer Platform of Highly Personalized Engagement

The age of generative AI has arrived, and is quickly gaining consumer acceptance. AI has the potential to revolutionize the internet by enabling highly personalized experiences for users, as evidenced by the early applications we are now seeing in edtech and search. By providing concise and natural language answers, language models have the potential to significantly improve search engines. Furthermore, edtech can now provide highly individualized learning plans on a large scale, giving students a “teacher in their pocket” who understands their specific needs and can provide personalized solutions to their learning requirements. AI chatbots are already being used for human connections, and many users find real meaning in their interactions with these bots. Overall, AI has the potential to supercharge existing products and create new product categories, thereby improving the consumer experience and making scaling easier. With the massive cost differential between humans doing this work and AI at scale it’s easy to see how this could potentially impact many industries.

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China’s Answer to ChatGPT Is Called ‘Ernie’

Baidu, the Chinese tech giant, is developing Ernie, China’s answer to ChatGPT. The AI-powered language model, abbreviated with the clunky “Enhanced Representation through Knowledge Integration,” has been in development since 2019 and is set to debut as a standalone service in March. Ernie can understand language, generate language, and generate images from text. Baidu intends to incorporate Ernie into its search engine in the future, similar to Microsoft’s strategy with ChatGPT and Bing. Due to the inability of many Western companies to operate in China, Ernie may be the first AI chatbot with which many Chinese internet users interact. Although its capabilities are unknown, Ernie is expected to be a strong competitor to ChatGPT and Bard after four years of development.

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Generative AI is building the foundation of proptech’s next disruptive wave

As most of my readers are aware, artificial intelligence (AI) has been making headlines and progress in a variety of industries in 2022 and now in 2023. With venture capitalists investing over $49 billion in AI, there is still significant room for growth in real estate tech or proptech. By creating more efficient and personalized experiences, AI will revolutionize the way proptech operates, from search and listings to mortgages and construction. AI-powered chatbots that can provide personalized consultations will disrupt traditional real estate brokerages. The mortgage market in the United States at more than $13 trillion will benefit from AI’s ability to create infinite customer personas for more robust search and underwriting. AI will also improve the customer journey from policy administration to claims management by automating the insurance layer for renters and homeowners. The incorporation of artificial intelligence in real estate technology represents a significant opportunity for entrepreneurs and innovation and massive disruption for the traditional marketplace.

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