Mediaboss Marketing

Alexa! What is Artificial Intelligence? Artificial Intelligence is the study of devices that perceive the environment and take action that maximize their chance of success at some goal, more commonly is used to describe when machines are seen as mimicking human cognitive functions such as learning and problem solving. Well, isnt that convenient.

Artificial intelligence (AI), a radical concept developed by computer scientists in the 1950s, has tremendous applications in our daily lives today. It has come to play a crucial role in manufacturing, healthcare, finance, marketing and more. Companies and people worldwide are relying on machine learning, robotics and artificial intelligence to improve their products, processes and customer experience. Whether its the cars we drive, computers that predict the weather, toys that learn to interact with children, or writing computer codes, AI is changing the way we live, work and play.

Artificial intelligence is based on the principles of human intelligence and is defined as the way in which machines imitate human intelligence to perform simple and complex tasks. Artificial intelligence aims to learn human cognitive abilities and eventually surpass it. Currently, most AI models rely on deep neural networks, inspired by the human brain, which takes in a lot of raw data and expected results and learns the relationship between the two. Once trained it can apply this knowledge to new data and predict the result. More advanced methods use Deep reinforcement learning, where the model learns to make decisions by trial and error. In 2017, AlphaGo based on Deep reinforcement learning beat Ke Jie, the number one ranked player in the world at the time in board game Go. The self-taught AlphaGo Zero achieved a 1000 victory against the early competitive version of AlphaGo, and is the best Go player in the world.

Artificial intelligence has given computers the skills and capabilities never seen before. These advancements have helped us to understand more about diseases and how we can treat them better, for instance last year when the Google attention-based neural network AlphaFold 2 demonstrated a result that would have taken decades for humans to reach. AlphaFold 2 was able to determine the 3D structure of a protein with an accuracy rivaling crystallography, the gold standard for convincingly modelling proteins. But unlike crystallography, which takes months to return results, AlphaFold 2 can model proteins in hours. In healthcare, advanced AI systems are helping doctors diagnose and treat diseases in patients faster and more accurately and perform robotic surgeries which are more accurate and efficient. In Fact, the biggest problem that humanity is facing today, the Covid crisis, was first alerted to us by the Candian AI Platform BlueDot on the new years eve. AI has led to the rise of Self-driving vehicles and drones and weve seen how they have fueled the chatbots to give customers a wholesome experience.

Artificial intelligence is a central premise of disruptive change in the Fourth Industrial Revolution (Industry 4.0), a revolution that challenges our notions of what it means to be human and is more transformative than any other industrial revolution we experienced. Simply put, artificial intelligence is learning to make decisions faster than humans. This is enabling us for the first time to bring automation in the service sector as computers get more comfortable in speaking, writing, reading and recognising more patterns. AI has created a number of tools that allow people to rethink how we integrate information, analyze data and use the results to improve decision-making.

Most of the AI we talked about is called Artificial Narrow Intelligence (ANI), machines which are extremely good at doing one task but cannot extend their capabilities to other tasks. ANI has already surpassed humans in terms of accuracy and speed in many tasks, and it is getting better fast. The next stage in the evolution of AI is Artificial General Intelligence (AGI). With AGI we could develop machines capable of understanding the world as well as any human, and with the same capacity to learn how to carry out a huge range of tasks.

In 2020, OpenAI developed GPT-3, a language model capable of performing numerous diverse tasks without specific training. While GPT-3 is not an example of AGI, it is considered by some to be too advanced to classify as a narrow AI system.

The two driving forces for exponential AI development have been data, more accessible than ever due to the internet, and cheap computation power. By 2030, we would have enough computation power that the idea of a machine capable of human intelligence would not seem impossible anymore.

AI is poised to have a profound impact on society, subsequently we also need to start thinking about all the implications. Today, technology is improving at a faster rate than our education and legal system can keep up. Regulations have to be put in place in what data is accessible to machines and what AI machines are allowed to do. Research has to be focused in directions where AI is helpful for humanity. Most of the dangerous, repeatable and strenuous jobs will be done by AI powered robots. What will this mean for us, for humanity? This will bring back jobs that require creativity, human presence and social and emotional intelligence and subjective decision making. Jobs of the future will require more collaboration as the computational work will be taken up by a program. Who knows, AI might be the trigger that brings back human touch in its true form.

As a final thought, a segment of this article was generated by AI. Can you tell the difference?

Views expressed above are the author's own.

END OF ARTICLE

See the article here:
Importance of Artificial Intelligence and its impact on humanity - The Times of India Blog

Introduction

Internet a world-changing invention that is involved in most of the things we do. When we talk about education in the modern-day, we cannot put aside the digital world. Online students can find legit writing services or, if they cant decide on an essay service, they can get reviews and see which are the best. Or they can get some help with different questions they might have. Teachers, on the other hand, also have quite a lot of resources to pick from. There are opportunities to learn more about classroom management, student motivation, interaction, etc.

When we talk about the digital world, though, we should pay some attention to artificial intelligence. This is a particular area of study that will grow more and more with the days to come.

Artificial Intelligence, or the so-called AI, is gaining more and more steam as we continue to innovate it. We encounter it in quite a lot of places in our day-to-day life, for instance, in applications as Alexa. We also already know that with the current pandemic we experienced a growth in digital education. So, how do we see AI in the future of education in general?

AI systems are such machines (or, perhaps, software) that can perform human-like tasks. By that, we mean that the algorithms behind them allow them to do tasks that are usually associated with people. AI systems rely on their algorithms for executing their functions. Via them, they examine the available information and reach conclusions. Once they reach such a conclusion, they then act. It can be perception, interaction, behavior reasoning, finding patterns, etc.

Through AI systems machines can perform high-level functions massively and rapidly. Sometimes they even resemble humans in their actions. Sure, this brings about not only excitement but also fear.

There is a view among some circles that AI can replace humans. But its also possible that AI will work together with people, helping them in their day-to-day life. When we talk about education, we want to point out that human interaction is key. Still, AI can offer some help for teachers by automating various routine tasks.

Teaching is a highly sensitive area. Student-teacher interaction is close contact. Teachers need to build a trusting relationship with their pupils. Also, some types of feedback require human interaction. Thus, we cannot talk about AI replacing teachers. We dont consider such a possibility for some tasks that require face-to-face contact.

But some repetitive tasks can be automated using AI systems. This will allow teachers to put more emphasis on complex activities.

AI can offer many possibilities for education. For instance, it can support teachers and collaborate with them. Of course, collaboration isnt said in the traditional human-to-human meaning. No, AI can rather help teachers gain more knowledge of the strong and weak sides of their students.

Yes, through the use of AI one can create specific assessments. They can then be used to allow teachers to understand how far along the material are their students. With such programs teachers can see which students excel where and where are the weak points.

Also, teachers have a lot of students to work with. They cannot pay attention to anyone all the time. So, in some cases, they will be working with specific students. Via AI, though, they can understand what is happening to other students at that time.

AI presents another opportunity, too. It can offer a way for students and teachers to collaborate better. It can also enhance the work-together skills of students.

When we are talking about complex problems and means of solving them, AI can help here, as well. It can boost the problem-solving skills of students and teachers alike both individually and as a group.

With AIs students can experience personalized learning. When a teacher is working with a class, personalized learning isnt an easy thing to achieve. But it can be done through AI systems. Those systems will allow customization of the learning process for the particular student.

Emotional well-being is something that is thought about, too. The emotional states of children impact how they learn. AI can help identify what is the emotional state of the students and give them support. Such support can be offered through gestures, words, or attempts at motivating the student.

Artificial Intelligence can be used in various applications. Some of them we are already familiar with. But there are also other opportunities. For instance, AI can be used in learning apps. By them, students can experience gameplay that is related to learning specific materials and/or skills. Like, they can be learning math while playing a certain AI-powered game. Or they can ask for help with homework and questions that bother them and receive automatic answers from other students. Such applications can be used to tailor personalized learning plans for every student.

Sure, there are still areas that will require human-to-human interaction. Thats for certain. But the introduction of AI into the classroom can help free teachers time for more important aspects. It can also improve the interaction in the classroom.

AI systems are certainly something that will grow even more with time elapsed. We should think about how they can affect the future of education.

They can do that in various ways. We mentioned some of the above, but we are certain that new and new inventions will arise. With all of them, we can get a better understanding of the learning process, how students interact with one another, of how teachers can tailor their study plans.

One huge plus is the opportunity for a personalized learning process. Teachers cannot be with everyone all the time. Their teaching methodology cannot be tailored to every single student on their own, or they will have no time for everyone. Here comes AI. That system offers to give us a way to suit the learning plans specifically to every student. This will allow kids to learn at their own pace, strengthen their weak sides, and get even better in their strong aspects. AI cannot replace teachers but can certainly teach us something.

Read more from the original source:
Artificial Intelligence and What Does It Mean for Education - Analytics Insight

Barcelona: Telefnicas chairman, Jos Mara lvarez-Pallete, used his speech on Monday during the first day of the Mobile World Congress, at the opening of a session organised by the GSMA and entitled 'Our Connected World', to highlight the potential and the opportunity that digital transformation represents. "This digital revolution is the once in a lifetime opportunity to reimagine the future. With great opportunities, comes great responsibility. Let us honor it," he emphasized.

Precisely in order to reinforce the historic moment that now presents itself both for the telecommunications sector and for society as a whole, lvarez-Pallete based his speech on three concepts: Relevance and Revolution through Reclamation.

Recalling all that has happened in the last year, which "has been like travelling in a time machine five years ahead in terms of adoption of technology", he highlighted the fact that telecommunications networks passed the test to which they were subjected. "When we were most needed, we were there," he said, reflecting the Relevance acquired by telecommunications companies. And, above all, he underlined the new world that is opening up for these networks, which "are no longer just carrying data but enabling the world of the Artificial Intelligence". " As much as a 40% of Internet traffic is non-human, generated by machines that are talking to each other", he pointed out as a demonstration of this new era in which digitization "is going to yield enormous amount of data that can be transformed into information by the Artificial Intelligence".

The challenge is to turn that data into knowledge, which requires "taking digitization to the next level, making it smart, letting Artificial Intelligence realise its full potential". He added: "This can only happen with the support of the next generation digital infrastructure and a solid telco sector whose Relevance to the economy and society is now more significant than ever.

In further detailing his approach, lvarez-Pallete has placed cutting-edge connectivity as "the first ingredient" of the new smart digitization. Next to it, as the second ingredient, "technologies like Edge Computing, Cloud, Cybersecurity, IoT and Big Data". And, as the last ingredient, the forecast of a substantial increase in data generated by digitization and transformed into information by Artificial Intelligence. "The real evolution lies there," said lvarez-Pallete.

Seizing it requires decisive action. "This is an extraordinary opportunity we cannot miss, but it is also a bog challenge. Governments need to attract investment in the smart digital infrastructure that will make all that possible," he said. And this response must come now, because there is no time to lose: "We need to react to keep up with the opportunity. To grab it, Europe needs a sustainable telco sector, otherwise we will lag further behind in the global race for digital leadership.

"We reclaim a new regulatory framework and competition rules to build a strong digital Europe", he demanded. This call proposes a necessary change to take full advantage of digitization as a transformative lever capable of generating growth, quality jobs, sustainability and inclusion.

These changes are what the current Digital Revolution can bring about, which, if well managed, will transcend its dimension and become an Intelligent Revolution. We need a new Digital Deal to manage the digital transition with values and people at the core" said lvarez-Pallete.

Driven by its mission to 'make our world more human by connecting lives', Telefnica promotes fair, inclusive and sustainable digitization, so that digital can also act as a unifying and cohesive backbone if it is conducted with a clear vision. "It is our collective responsibility to future generations to spread the benefits of digitization and make sure that we do not leave anyone behind. Inequality of opportunities is the major challenge we are facing," he warned.

This need to combine the potential of digitization and connectivity with values and people is evident in the processing and management of data, which in this revolution has become a new production factor that is absolutely key because of the sensitive information it contains. "Our privacy and our individual data are part of our dignity. We have the right to know who is using it and how, how much it is worth and who benefits from their value", said Telefnicas chairman.

lvarez-Pallete's speech took place during the first of four days of this year's Mobile Congress. Telefnica is attending the Congress in person, with a 952 square metre stand, and with an extensive virtual proposal, reflected in a twin or digital stand through which all the latest news on the company's participation in the MWC can be followed. In total, the Group will showcase up to 34 customer success stories that will showcase the solutions, services and applications with which Telefnica supports companies, sectors and public administrations in their digital and technological transformation.

Read the original post:
lvarez-Pallete: "We must take digitization to the next level with Artificial Intelligence" - TelecomTV

DUBLIN, June 28, 2021--(BUSINESS WIRE)--The "Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2021" report has been added to ResearchAndMarkets.com's offering.

The Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2021 report provides an understanding and access to the artificial intelligence partnering deals and agreements entered into by the world's leading healthcare companies.

Trends in artificial intelligence partnering deals

Disclosed headlines, upfronts, milestones and royalties by stage of development

Artificial intelligence partnering contract documents

Top artificial intelligence deals by value

The Global Artificial Intelligence (AI) Partnering Terms and Agreements 2010 to 2021 report provides an understanding and access to the artificial intelligence partnering deals and agreements entered into by the world's leading healthcare companies.

The report provides a detailed understanding and analysis of how and why companies enter artificial intelligence partnering deals. The majority of deals are early development stage whereby the licensee obtains a right or an option right to license the licensor's artificial intelligence technology or product candidates. These deals tend to be multicomponent, starting with collaborative R&D, and commercialization of outcomes.

This report provides details of the latest artificial intelligence, oligonucletides including aptamers agreements announced in the healthcare sectors.

Understanding the flexibility of a prospective partner's negotiated deals terms provides critical insight into the negotiation process in terms of what you can expect to achieve during the negotiation of terms. Whilst many smaller companies will be seeking details of the payments clauses, the devil is in the detail in terms of how payments are triggered - contract documents provide this insight where press releases and databases do not.

Story continues

For example, analyzing actual company deals and agreements allows assessment of the following:

What is actually granted by the agreement to the partner company?

What exclusivity is granted?

What are the precise rights granted or optioned?

What is the payment structure for the deal?

How are sales and payments audited?

What is the deal term?

How are the key terms of the agreement defined?

How are IPRs handled and owned?

Who is responsible for commercialization?

Who is responsible for development, supply, and manufacture?

How is confidentiality and publication managed?

How are disputes to be resolved?

Under what conditions can the deal be terminated?

What happens when there is a change of ownership?

What sublicensing and subcontracting provisions have been agreed?

Which boilerplate clauses does the company insist upon?

Which boilerplate clauses appear to differ from partner to partner or deal type to deal type?

Which jurisdiction does the company insist upon for agreement law?

The initial chapters of this report provide an orientation of artificial intelligence dealmaking and business activities. Chapter 1 provides an introduction to the report, whilst chapter 2 provides an overview of the trends in artificial intelligence dealmaking since 2010, including details of average headline, upfront, milestone and royalty terms.

Chapter 3 provides a review of the leading artificial intelligence deals since 2010. Deals are listed by headline value, signed by big pharma, most active artificial intelligence dealmaking companies. Where the deal has an agreement contract published at the SEC a link provides online access to the contract.

Chapter 4 provides a comprehensive listing of the top 25 most active companies in artificial intelligence dealmaking with a brief summary followed by a comprehensive listing of artificial intelligence deals, as well as contract documents available in the public domain. Where available, each deal title links via Weblink to an online version of the actual contract document, providing easy access to each contract document on demand.

Chapter 5 provides a comprehensive and detailed review of artificial intelligence partnering deals signed and announced since Jan 2010, where a contract document is available in the public domain. The chapter is organized by company A-Z, deal type (collaborative R&D, co-promotion, licensing, etc.), and specific therapy focus. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

Chapter 6 lists artificial intelligence deals by technology type.

Chapter 7 provides a comprehensive and detailed review of artificial intelligence partnering deals signed and announced since Jan 2010. The chapter is organized by specific artificial intelligence technology type in focus. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

In addition, a comprehensive appendix is provided organized by artificial intelligence partnering company A-Z, deal type definitions and artificial intelligence partnering agreements example. Each deal title links via Weblink to an online version of the deal record and where available, the contract document, providing easy access to each contract document on demand.

The report also includes numerous tables and figures that illustrate the trends and activities in artificial intelligence partnering and dealmaking since 2010.

In conclusion, this report provides everything a prospective dealmaker needs to know about partnering in the research, development and commercialization of artificial intelligence technologies and products.

Key Topics Covered:

Executive Summary

Chapter 1 - Introduction

Chapter 2 - Trends in artificial intelligence dealmaking

Chapter 3 - Leading artificial intelligence deals

Chapter 4 - Most active artificial intelligence dealmakers

Chapter 5 - Artificial intelligence contracts dealmaking directory

Chapter 6 - Artificial intelligence dealmaking by technology type

Chapter 7 - Partnering resource center

For more information about this report visit https://www.researchandmarkets.com/r/lyklma

View source version on businesswire.com: https://www.businesswire.com/news/home/20210628005698/en/

Contacts

ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com

For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

Go here to read the rest:
Global Artificial Intelligence in Healthcare: Deals and Agreements by Leading Players From 2010-2021 - ResearchAndMarkets.com - Yahoo Finance

We have enjoyed the power of technology in the past few decades, and we saw it progress. From the gadgets that we use daily to make our life more convenient to the medical field and healthcare, we have been enjoying the technology of artificial intelligence to make things easier.

AI in healthcare benefits both medical practitioners and patients alike. Lets dive in on how were using this and how we can use it in the future.

RELATED: AI Applications for Clinical Trials Increase, Refining Endpoints, Quantifying Pain, & More

The future of healthcare is here as we are using artificial intelligence in diagnostics and treatment. It could only mean that we can expect the advancements in technology in this field to rise further and faster.

Here are some examples of how we apply artificial intelligence in healthcare:

Medical practitioners use AI in healthcare from the smallest scale to the biggest and most crucial ones, such as dealing with high-risk diseases. On a small scale, patients use telehealth thru computers and mobile devices.

There are telehealth tools used for documentation, recording metrics, and process of information. These are commonly used from home.

Especially in times like these, going out of your home can be a threat because of the pandemic. Telemedicine is one of the best options, especially for those who need immediate care.

Doctors and physicians use AI on patients to detect early signs of stroke, cancer, neurological, or cardiovascular disorders by recording algorithms. This way, the computer can see the trends and activity of a persons organs to catch and cure a potential disease before it can pose a threat.

IBM recently partnered with Pfizer to develop an AI machine that can detect the early onset of Alzheimers disease in a person. The test evaluates cognitive impairment in various neurological disorders, including stroke and Alzheimers disease.

In addition to helping with diagnosis and prevention, AI can also be used by physicians as their assistants when dealing with patients.

A study revealed that physicians spend almost half of their work time dealing with data in Electronic Health Records (EHR). Primary care physicians can focus on dealing with the patients more since computers can now take notes for them, analyze discussions with the patients, and enter the necessary information into the EHRs.

In addition to this, science now uses voice recognition and speech dictation to make clinical tasks possible through natural language processing. It is a process where the computer catches the commands given by a person and converts that into data.

In relationship with the use of EHR, AI can help treat patients through personalized medicine. With all the records stored in the computer, the computer can identify large quantities of data to identify treatment options instantly based on a patients background.

The precise and quick process of drug development and clinical trials are now possible because of AI.

Computers and artificial intelligence can help clinicians work efficiently and lead to more precise diagnoses at the clinical level.

Valence Discovery recently used machine learning and artificial intelligence in their healthcare institution for molecular property prediction and multiparameter optimization for preclinical drug discovery to Charles Rivers patients.

RELATED: AI in Biopharma: Deep Genomics and BioMarin Forge Pact; InterVenn Raises $34 Million

Wearable technology like smartwatches or even smartphones can detect oxygen levels, heart rate, and even violent falls.

These devices can even directly call emergency if it reaches critical level making these smart devices a reliable way to prevent serious conditions.

Most useful to dermatologists or ophthalmologists, using a smartphone to take selfies for diagnostic is being used to treat and examine patients, especially in this day and age.

With the popularity of phone-in check-ups during this pandemic, using this technology for clinical improvements and diagnosis can be considered a step-up for healthcare using technology.

Inserting smart device capabilities on hospital machines and devices can help doctors detect an early sign of a patients critical condition through algorithms and patterns.

When were talking about integrating disparate data from across the healthcare system, integrating it, and generating an alert that would alert an ICU doctor to intervene early on the aggregation of that data is not something that a human can do very well, Executive Director of the MGH & BWH Center for Clinical Data Science Mark Michalski, MD said in an interview.

How can technology help a person deal with pain, you ask? Artificial intelligence combined with virtual reality is being used as pain management tools by some companies.

Clinics and hospitals can create simulated realities to distract patients from their pain and even an opioid crisis.

Johnson & Johnson Reality Program is the first company to do this and is expected to become a trend and be used by other clinics or hospitals.

As a prediction by medical experts, obtaining tissues and other radiology tools will be improved through AI.

If non-invasive tools like x-rays, MRI machines, and CT scans are for internal visibility of the body, and biopsies are created to collect tissue samples from organs, the future, with the development of using AI technology, can do these things without being invasive or cause any harm from patients.

We want to bring together the diagnostic imaging team with the surgeon or interventional radiologist and the pathologist, MD Brigham & Womens Hospital Director of Image-Guided Neurosurgery Alexandra Golby said in an interview. That coming together of different teams and aligning goals is a big challenge.

If we want the imaging to give us information that we presently get from tissue samples, then were going to have to be able to achieve very close registration so that the ground truth for any given pixel is known.

Technology and artificial intelligence in healthcare have been very vital in its progress. It has been a major help with drug discovery and the recognition of diseases.

As researchers continue to discover new technology, the medical field, doctors, and patients will benefit from its advancements.

Read more:
Artificial Intelligence In Healthcare And How It's Transforming The Industry - BioSpace