BIG DATA WITH DINO PEDRESCHI: THE AGE OF DATA


The age of data

Dino Pedreschi, Professor of Computer Science at the University of Pisa and co-lead of KDD Lab - Knowledge Discovery and Data Mining Laboratory, talks about big data, machine learning and intelligent systems.

Teresa Guerrero

Data science is a term used for dealing with big data that includes data collection, cleansing, preparation and analysis for various purposes. A data scientist collects data from multiple sources and after analysis applies into predictive analysis or machine learning and sentiment analysis to extract the critical information from the data sets. These data scientists analysis and understand the data from business perspective and give useful insights and accurate predictions that can be used while taking critical business decisions.

Kaan Buğra Kundakçı

In response to Nikoleta Stavros

Data science is a pretty ambiguous, ill-defined term and interdisciplinary field; and people mean (expect) different things in different contexts. In my opinion, in practice, data science is pretty much the same as what we've known as data mining or KDD (Knowledge Discovery in Databases).

The typical skills of a data scientists are

  • Computer science: programming, hardware understanding, etc.
  • Math: Linear algebra, calculus, statistics
  • Communication: visualization and presentation
  • Domain knowledge
Nikoleta Stavros

Data science is a pretty ambiguous, ill-defined term and interdisciplinary field; and people mean (expect) different things in different contexts. In my opinion, in practice, data science is pretty much the same as what we've known as data mining or KDD (Knowledge Discovery in Databases).

Doriane Mateu Phạm

In generative models, the AI is more complex and doesn't rely on a previously collected database of answers. They respond to queries with newly generated code or phrases. These models can be used to simulate wide areas of conversation in chat bots or deal with new situations in general much more capably. These models simulate conversation with humans on broader topics better than retrieval-based systems but may make grammatical errors and also can be taught poor responses. 

Dorothea Petrescu

John McCarthy, an American computer scientist, coined the term "artificial intelligence" in 1956 at the Dartmouth Conference where the discipline was born. Today, it is an umbrella term that encompasses everything from robotic process automation to actual robotics. It has gained prominence recently due, in part, to big data, or the increase in speed, size and variety of data businesses now collect. AI can perform tasks such as identifying patterns in data more efficiently than humans, enabling businesses to gain more insight from their data.

Denny Daskalov

In response to Gunnr Østergård

The application of AI in the realm of self-driving cars also raises ethical concerns. When an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing it to make ethical decisions about how to minimize damage.

Gunnr,

Another major concern is the potential for abuse of AI tools. Hackers are starting to use sophisticated machine learning tools to gain access to sensitive systems, complicating the issue of security beyond its current state. Deep learning-based video and audio generation tools also present bad actors with the tools necessary to create so-called deepfakes, convincingly fabricated videos of public figures saying or doing things that never took place.

Gunnr Østergård

The application of AI in the realm of self-driving cars also raises ethical concerns. When an autonomous vehicle is involved in an accident, liability is unclear. Autonomous vehicles may also be put in a position where an accident is unavoidable, forcing it to make ethical decisions about how to minimize damage.

Jalen Sepi Ozols

Artificial intelligence based home automation is the future. If everyone in the United States installed Nest or a similar smart thermostat, they would collectively save hundreds of millions of dollars annually in wasted energy since Nest is able to “learn” when people are or are not home. Nest and others automatically adjust temperature saving on energy use and costs.

Svetlana Barbieri

I believe it will be more like the science fiction movies, where we will maintain and work with the machines that do the work. However, these “jobs” will come with a level of prestige, as most people will probably live off a government sponsored socialism system. With AI and automation replacing so many jobs in the next 20 years, we will have to change social systems in order to adapt.

Prof. Dr.-Ing. Helga Breitner

With each wave of technology advancement, the quality of life for the world overall has increased. With AI, we will have better personalized healthcare, more efficient energy use, enhanced food production capabilities, improved jobs with less mundane work, and more. People will lead longer and more high quality lives.

Janko Kyllikki

One of the top benefits will be the emergence of personalized medicine. Rather than a one-size-fits-all approach, doctors will be able to tailor treatment on an individual basis and prescribe the right treatments and procedures based on your medical history. As far as living up to hype, yes — definitely. Though as with many new technologies it’s more of a question of “when” rather than “if.”

Chares Valentinianus Kavanaugh

In response to Jovanka Pokorny

Many high school and college students are familiar with services like Turnitin, a popular tool used by instructors to analyze students’ writing for plagiarism. While Turnitin doesn’t reveal precisely how it detects plagiarism, research demonstrates how ML can be used to develop a plagiarism detector.

The biggest change that’s coming is the move from humans using software as a tool, to humans working with software as team members. Software will monitor things, alert humans, and execute basic tasks without human intervention. This will free human time for the really creative or interesting tasks and greatly improve business. A.I. is going to have a much larger impact than the hype.

Jovanka Pokorny

Many high school and college students are familiar with services like Turnitin, a popular tool used by instructors to analyze students’ writing for plagiarism. While Turnitin doesn’t reveal precisely how it detects plagiarism, research demonstrates how ML can be used to develop a plagiarism detector.

Juniper Womack

IoT provides new opportunities for companies to solve customer issues instantly and pre-empt problems before they escalate. Continuous monitoring enables companies to anticipate -- and fix -- problems before the customer is aware of them. "Companies can remotely monitor mission-critical machinery and pre-emptively intervene, which prevents or reduces problems and lowers costs," Leggett said. For example, New England Biomedical Services Inc. uses IoT to monitor science lab usage of their recombinant and native enzymes for genomic research so they can restock supplies immediately.

Waclaw Piatek

The term big data was first used to refer to increasing data volumes in the mid-1990s. In 2001, Doug Laney, then an analyst at consultancy Meta Group Inc., expanded the notion of big data to also include increases in the variety of data being generated by organizations and the velocity at which that data was being created and updated. Those three factors -- volume, velocity and variety -- became known as the 3Vs of big data, a concept Gartner popularized after acquiring Meta Group and hiring Laney in 2005.

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