- Because we know how to have fun âď¸, we were (litteraly) excited about spending days and nights on crunching data of European startups funded in 2016 to eventually get a real sense of what is AI and Dataâs real trend in Europe.
- 2800+ Startups later, we eventually found out 271 AI Data startups and here is our main conclusion: Yes, AI is a thing and itâs happening now.Not convincing enough?
- Fundraising went crazy, and we always want more of itNumbers staggerÂ : $774 millionâââYes 7â7 and 4, nearly 10% of the total 10+ billion invested in European startups in 2016, has been fully dedicated to AI data.
- Bringing the total investment in AI Data to 2 billion since 2014.2.
- This trend has been led by early stage investments which played a signifiant role: $215 million have been invested in 171 early stage startups (0 to $5m in funding).
Because we know how to have fun ✌️, we were (litteraly) excited about spending days and nights on crunching data of European startups funded in 2016 to eventually get a real sense of what is AI and…
Continue reading “The AI Rush – Serena Capital”
- Genus AI will use the money to expand its technology team in London and boost its sales operations in the US – the startup’s primary market.
- Despite increasing amount of data and computing power organisations are still struggling to engage with customers in an authentic way,” said Tadas Jucikas, CEO and co-founder of Genus AI.
- “At Genus AI we are building a new kind of artificial intelligence system which helps us inform and have a positive impact on the real world.
- Our technology has been in development with our customers for almost two years and I am extremely excited to welcome our new investors to help us bring Genus AI to the next level of growth,” he continued.
- Set up alongside Brent Clickard and Tobias Kloepper, Genus AI leverages machine learning, neuroscience, psychology and behavioural sciences to enable customers to engage with brands in an emotionally intelligent way.
The round was led by early-stage technology investment firm Picus Capital.
Continue reading “Artificial intelligence startup Genus AI scores $1m”
- The creators of Unity, the most popular game engine in the world, recently launched a set of machine-learning tools that lay the groundwork for actual AI (not scripted computer opponents) in video games.
- Typically these kits include rendering aids and simple tools for training neural networks, but the beta release sent to developers promises to revolutionize video games, and provides machine-learning researchers with a perfect environment for training robot brains.
- Unity provides developers with the tools to create machine-learning agents capable of learning and interacting with each other in a virtual world, which makes it possible to create games inhabited by AI that actually learns, instead of forcing developers into painstakingly scripting behavior by hand.
- Video game developers have been using the term “artificial intelligence” (AI) since the 1950s to describe a computer opponent designed to challenge humans.
- This use of the term has no relation to machine-learning; the AI in a video game doesn’t learn anything, it simply executes algorithms.
Unity developers recently got an AI upgrade in the form of machine-learning tools that provide game and AI programmers with next generation capabilities.
Continue reading “AI isn’t just learning to play video games, it’s helping us build them”
- I have not seen any significant use of AI in my own clinical practice during my time in Boston, but exciting developments in the last two years hold much promise.
- One of the potential benefits when integrating AI into medical practice is improvement of clinical decision making and diagnosis.
- The concept of using AI to provide clinical decision support systems for physicians has been studied in some medical specialties with varying degrees of effectiveness.
- Comparisons between the paradigms of machine learning based, knowledge based, and hybrid methods have not yielded a clear model on how AI best uses clinical data to arrive at a diagnosis.
- There is promise that Deep Learning methodology will allow for AI to train much like a medical resident does through a large data set of disease presentations.
A discussion on Dr. Michael Forsting’s article “Machine Learning Will Change Medicine” in the Journal of Nuclear Medicine.
Continue reading “Medicine in the Age of AI”
- Demis Hassabis knows a thing or two about artificial intelligence: he founded the London-based AI startup DeepMind, which was purchased by Google for $650 million back in 2014.
- In a paper published today in the journal Neuron, Hassabis and three coauthors argue that only by better understanding human intelligence can we hope to push the boundaries of what artificial intellects can achieve.
- But it also points out that more recent advances haven’t leaned on biology as effectively, and that a general intelligence will need more human-like characteristics—such as an intuitive understanding of the real world and more efficient ways of learning.
- As Hassabis explains in an interview with the Verge, artificial intelligence and neuroscience have become “two very, very large fields that are steeped in their own traditions,” which makes it “quite difficult to be expert in even one of those fields, let alone expert enough in both that you can translate and find connections between them.”
- (Read more: Neuron, The Verge, “Google’s Intelligence Designer,” “Can This Man Make AI More Human?”)
Inquisitiveness and imagination will be hard to create any other way.
Continue reading “Google’s AI Guru Says That Great Artificial Intelligence Must Build on Neuroscience”
- But the transformational nature of artificial intelligence requires new metrics of success for our profession.
- This year alone at least 1 billion people will be touched in some way by artificial intelligence, which is transforming everything from financial services to transportation, energy, education and retail.
- And why IBM is a founding member of the Partnership on AI, a collaboration among Google, Amazon, Facebook, Microsoft, Apple and many scientific and nonprofit organizations charged with guiding the development of artificial intelligence to the benefit of society.
- Opportunity: Developers of AI applications should accept the responsibility of enabling students, workers and citizens to take advantage of every opportunity in the new economy powered by cognitive systems.
- They should help them acquire the skills and knowledge to engage safely, securely and effectively in a relationship with cognitive systems, and to perform the new kinds of work and jobs that will emerge in a cognitive economy.
By Guru Banavar, IBM’s Chief Science Officer for Cognitive Computing
I am a computer scientist and engineer, inspired by the art of the possible an…
Continue reading “The Science of AI and the Art of Social Responsibility”
Researchers have successfully given AI a curiosity implant, which motivated it to explore a virtual environment.
Continue reading “Researchers Have Created an AI That Is Naturally Curious”