AI and its applications are not going away and will cause a significant amount of change to everyday life over the next decade. Whilst there has been a lot of buzz in the past that has not been fulfilled, advances in skills, computing power and modelling and ensuring that the hype is finally being realised. To some extent, we don’t even know what AI is capable of yet which is both exciting and scary!
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka!
Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
AI vs Machine Learning vs Deep Learning | Machine Learning Training with Pyth...Edureka!
Machine Learning Training with Python: https://www.edureka.co/python )
This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python Blog: https://goo.gl/fe7ykh ) on "AI vs Machine Learning vs Deep Learning" talks about the differences and relationship between AL, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:
1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning
Machine Learning Tutorial Playlist: https://goo.gl/UxjTxm
Differences Between Machine Learning Ml Artificial Intelligence Ai And Deep L...SlideTeam
"You can download this product from SlideTeam.net"
Differences between Machine Learning ML Artificial Intelligence AI and Deep Learning DL is for the mid level managers to give information about what is AI, what is Machine Learning, what is deep learning, Machine learning process. You can also know the difference between Machine learning and Deep learning to understand AI, ML, and DL in a better way for business growth. https://bit.ly/325zI9o
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
A seminar ppt fully imformative about ai.1. Artificial Intelligence<br />Shannon Baker, Laura Paviglianiti, Tim Stuart, Harrison Baker<br />
2. What is Artificial Intelligence?<br />
3. The intelligence of machines and the branch of computer science that aims to create it<br />"the study and design of intelligent agents”<br />No single goal of artificial intelligence<br />Some say it’s putting the human mind into computers<br />What is intelligence?<br />The computational part of the ability to achieve goals in the world<br />We do not yet fully understand what intelligence consists of<br />
4. 1941:Development of the electronic computer<br /><ul><li>Some trace the origin to John Atanasoff and Clifford Berry at Iowa State University
5. Required large, separate </li></ul>air-conditioned rooms<br /><ul><li>Required separate </li></ul>configuration of <br />thousands of wires<br /><ul><li>Data fed into system </li></ul>By punched cards<br />
6. First Commercial, Stored Program Computer<br />Made job of entering a program easier<br />Advancements in computer theory computer science <br />(and eventually <br />to AI)<br />Invention of a <br />means of processing <br />data makes AI <br />possible<br />
7. Dartmouth Conference<br />John McCarthy (“father of AI”) organizes conference<br />A month of brainstorming in VT<br />Talent and expertise of others interested in machine intelligence<br />Biggest gain: field <br />now called<br />Artificial Intelligence<br />
8. LISP Language Developed<br />McCarthy announces new development: LISP language<br />Still used today<br />LISt Processing – <br />language of <br />choice <br />among AI <br />developers<br />
The slide helps to get an insight on the concepts of Artificial Intelligence.
The topics covered are as follows,
* Concept of AI
* Meaning of AI
* History of AI
* Levels of AI
* Types of AI
* Applications of AI - Agriculture, Health, Business (Emerging market), Education
* AI Tools and Platforms
Natural language processing provides a way in which human interacts with computer / machines by means of voice.
"Google Search by voice is the best example " which makes use of natural language processing..
The UAE AI Strategy: Building Intelligent EnterprisesSaeed Al Dhaheri
This presentation was presented at the CIOMajlis meeting and highlights the UAE AI strategy and how to build Intelligent AI-driven Enterprises. Examples of some AI applications in the UAE public sector were highlighted.
Functionalities in AI Applications and Use Cases (OECD)AnandSRao1962
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It covers the methodology for assessing AI use cases by technology, value chain, use, business impact, business value, and effort required.
Differences Between Machine Learning Ml Artificial Intelligence Ai And Deep L...SlideTeam
"You can download this product from SlideTeam.net"
Differences between Machine Learning ML Artificial Intelligence AI and Deep Learning DL is for the mid level managers to give information about what is AI, what is Machine Learning, what is deep learning, Machine learning process. You can also know the difference between Machine learning and Deep learning to understand AI, ML, and DL in a better way for business growth. https://bit.ly/325zI9o
Data science is different from Data Analytics,Data Engineering,Big Data.
Presentation about Data Science.
What is Data Science its process future and scope.
Data Science Presentation By Amit Singh.
"Sexiest job of 21st century"
A seminar ppt fully imformative about ai.1. Artificial Intelligence<br />Shannon Baker, Laura Paviglianiti, Tim Stuart, Harrison Baker<br />
2. What is Artificial Intelligence?<br />
3. The intelligence of machines and the branch of computer science that aims to create it<br />"the study and design of intelligent agents”<br />No single goal of artificial intelligence<br />Some say it’s putting the human mind into computers<br />What is intelligence?<br />The computational part of the ability to achieve goals in the world<br />We do not yet fully understand what intelligence consists of<br />
4. 1941:Development of the electronic computer<br /><ul><li>Some trace the origin to John Atanasoff and Clifford Berry at Iowa State University
5. Required large, separate </li></ul>air-conditioned rooms<br /><ul><li>Required separate </li></ul>configuration of <br />thousands of wires<br /><ul><li>Data fed into system </li></ul>By punched cards<br />
6. First Commercial, Stored Program Computer<br />Made job of entering a program easier<br />Advancements in computer theory computer science <br />(and eventually <br />to AI)<br />Invention of a <br />means of processing <br />data makes AI <br />possible<br />
7. Dartmouth Conference<br />John McCarthy (“father of AI”) organizes conference<br />A month of brainstorming in VT<br />Talent and expertise of others interested in machine intelligence<br />Biggest gain: field <br />now called<br />Artificial Intelligence<br />
8. LISP Language Developed<br />McCarthy announces new development: LISP language<br />Still used today<br />LISt Processing – <br />language of <br />choice <br />among AI <br />developers<br />
The slide helps to get an insight on the concepts of Artificial Intelligence.
The topics covered are as follows,
* Concept of AI
* Meaning of AI
* History of AI
* Levels of AI
* Types of AI
* Applications of AI - Agriculture, Health, Business (Emerging market), Education
* AI Tools and Platforms
Natural language processing provides a way in which human interacts with computer / machines by means of voice.
"Google Search by voice is the best example " which makes use of natural language processing..
The UAE AI Strategy: Building Intelligent EnterprisesSaeed Al Dhaheri
This presentation was presented at the CIOMajlis meeting and highlights the UAE AI strategy and how to build Intelligent AI-driven Enterprises. Examples of some AI applications in the UAE public sector were highlighted.
Functionalities in AI Applications and Use Cases (OECD)AnandSRao1962
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It covers the methodology for assessing AI use cases by technology, value chain, use, business impact, business value, and effort required.
Travis Cox, Kathy Applebaum, and Kevin McClusky from Inductive Automation will discuss key concepts and best practices, show demos, and answer questions from the audience, to help you start integrating ML into your day-to-day processes.
Learn more about:
• Practical ways to use ML in your factory or facility
• What you'll need to get started
• Existing ML tools and platforms
• And more
An AI Maturity Roadmap for Becoming a Data-Driven OrganizationDavid Solomon
The initial version of a maturity roadmap to help guide businesses when adopting AI technology into their workflow. IBM Watson Studio is referenced as an example of technology that can help in accelerating the adoption process.
Travis Cox, Kathy Applebaum, and Kevin McClusky from Inductive Automation will discuss key concepts and best practices, show demos, and answer questions from the audience, to help you start integrating ML into your day-to-day processes.
Learn more about:
• Practical ways to use ML in your factory or facility
• What you'll need to get started
• Existing ML tools and platforms
• And more
Webinar: Machine Learning para MicrocontroladoresEmbarcados
Neste webinar, serão apresentados conceitos sobre inteligência artificial, assim como ferramentas disponíveis para o desenvolvimento integradas ao MPLAB X e ao Harmony 3 e demonstração de um sistema de detecção de anomalia utilizando um microcontrolador da família ATSAMD21 (ARM Cortex M0+).
[DSC Europe 22] On the Aspects of Artificial Intelligence and Robotic Autonom...DataScienceConferenc1
Autonomy in targeting is a function that could be applied to any intelligent system, in particular the rapidly expanding array of robotic systems, in the air, on land and at sea – including swarms of small robots. This is an area of significant investment and emphasis for many armed forces, and the question is not so much whether we will see more intelligent robots, but whether and by what means they will remain under human control. Today’s remote-controlled weapons could become tomorrow’s autonomous weapons with just a software upgrade. The central element of any future autonomous weapon system will be the software. Military powers are investing in AI for a wide range of applications10 and significant efforts are already underway to harness developments in image, facial and behavior recognition using AI and machine learning techniques for intelligence gathering and “automatic target recognition” to identify people, objects or patterns. Although not all autonomous weapon systems incorporate AI and machine learning, this software could form the basis of future autonomous weapon systems.
IBM i & digital transformation - Presentation & basic demo
IBM Watson Studio, IBM DSX Local w/ Open Source (Spark) & IBM Technology (OpenPower, CAPI, NVLINK)
Top machine learning trends for 2022 and beyondArpitGautam20
Exciting Machine Learning Trends that will emerge in 2022 & beyond and redefine the way ML Models & ML Technologies are used by enterprises. https://arsr.tech/top-machine-learning-trends-for-2022-and-beyond/
Artifical intelligence and the future of gcc governmentsSaeed Al Dhaheri
This talk was presented during the 24th GCC smart government and smart cities conference in Dubai on 22nd April 2018. It discusses the impact of AI on the GCC economy, providing use cases for AI from the UAE government and what the GCC countries need to do to benefit from AI.
IBM's Watson is a machine-learning platform that’s been built to mirror the same learning process that humans have: Observe, Interpret, Evaluate and Decide. Through the use of this cognitive framework, Watson can search through a database of information and pull out key insights to bridge gaps in human knowledge. It’s expertise scaling for enterprise.
Watson has already helped businesses across a variety of industries increase their customer engagement, data discovery and informed decision making abilities. Is your business next?
Companies that understand how to apply AI will scale and win their respective markets over the next decade. That said, delivering on this promise and managing machine learning projects is much harder than most people anticpate. Many organizations hire teams of PhDs and data scientists, then fail to ship products that move business metrics. The root cause is often a lack of product strategy for AI, or the failure to adapt their product development processes to the needs of machine learning systems. This talk will cover some of the common ways machine learning fails in practice, the tactical responsibilities of AI product managers, and how to approach product strategy for AI.
Peter Skomoroch, former Head of Data Products at Workday and LinkedIn, will describe how you can navigate these challenges to ship metric moving AI products that matter to your business.
Peter will provide practical advice on:
* The role of an AI Product Manager
* How to evaluate and prioritize your AI projects
* The ways AI product management differs from traditional product management
* Bridging the worlds of design and machine learning
* Making trade offs between data quality and other business metrics
Top Business Intelligence Trends for 2016 by Panorama SoftwarePanorama Software
10 top BI trends for 2016 – by Panorama
Its all about the insight
Visual perception rules
The learning suggestive system - AI gets real
The data product chain becomes democratized
Cloud (finally)
“Mobile”
Automated data integration
Interned of things data accelerating into reality
Hadoop accelerators are the last chance for Hadoop
Fading of the centralized on–premise DWH
Machine Learning Development Company in MohaliEllocent Labs
Ellocent Labs is a leading machine learning development company that leverages cutting-edge technologies to drive innovation and transformation. Our expert team specializes in developing custom machine learning solutions tailored to meet the unique needs of businesses across various industries. With a focus on advanced algorithms and data analytics, we empower organizations to harness the power of machine learning for predictive analytics, natural language processing, computer vision, and more. From concept to deployment, we ensure seamless integration and optimization, enabling businesses to unlock new opportunities, streamline operations, and stay ahead in today's dynamic market.
Similar to The Top Trends in Artificial Intelligence (20)
ER(Entity Relationship) Diagram for online shopping - TAEHimani415946
https://bit.ly/3KACoyV
The ER diagram for the project is the foundation for the building of the database of the project. The properties, datatypes, and attributes are defined by the ER diagram.
Multi-cluster Kubernetes Networking- Patterns, Projects and GuidelinesSanjeev Rampal
Talk presented at Kubernetes Community Day, New York, May 2024.
Technical summary of Multi-Cluster Kubernetes Networking architectures with focus on 4 key topics.
1) Key patterns for Multi-cluster architectures
2) Architectural comparison of several OSS/ CNCF projects to address these patterns
3) Evolution trends for the APIs of these projects
4) Some design recommendations & guidelines for adopting/ deploying these solutions.
1.Wireless Communication System_Wireless communication is a broad term that i...JeyaPerumal1
Wireless communication involves the transmission of information over a distance without the help of wires, cables or any other forms of electrical conductors.
Wireless communication is a broad term that incorporates all procedures and forms of connecting and communicating between two or more devices using a wireless signal through wireless communication technologies and devices.
Features of Wireless Communication
The evolution of wireless technology has brought many advancements with its effective features.
The transmitted distance can be anywhere between a few meters (for example, a television's remote control) and thousands of kilometers (for example, radio communication).
Wireless communication can be used for cellular telephony, wireless access to the internet, wireless home networking, and so on.
This 7-second Brain Wave Ritual Attracts Money To You.!nirahealhty
Discover the power of a simple 7-second brain wave ritual that can attract wealth and abundance into your life. By tapping into specific brain frequencies, this technique helps you manifest financial success effortlessly. Ready to transform your financial future? Try this powerful ritual and start attracting money today!
3. Where are we now?
Why AI is powerful now:
- Big Data
- Computing Power
- Models and Algorithms
4. My Top 5 Trends in
Artificial Intelligence
• Some of the top trends as we move towards 2020:
• Machine and Deep Learning
• Computer Vision
• The Cloud
• IoT at the “Edge”
• Automated Machine Learning (AutoML)
5. Machine and Deep
Learning
• Machine learning models start out dumb and get
smart by being exposed to data
• ML is algorithms and statistical models to
perform a specific task without explicit
instructions, relying on patterns and inference
• Using data to make business decisions based on
predicted outcomes
• Deep Learning is ML on steroids, used by
autonomous vehicles, content creation
6. Computer Vision
• Enables computers and devices to see, observe
and understand what they see
• The flood of visual information from modern
devices, sensors and technology has been key for
the development of CV technology
• Pre-trained algorithms are useful and widely
available
• Essential technologies: Deep Learning and
Convolutional Neural Network (CNN)
7. Computer Vision
• Enables computers and devices to see, observe
and understand what they see
• The flood of visual information from modern
devices, sensors and technology has been key for
the development of CV technology
• Pre-trained algorithms are useful and widely
available
• Essential technologies: Deep Learning and
Convolutional Neural Network (CNN)
8. The Cloud
• AI and ML algorithms needs data, a lot of data
• Local data centers available
• Large vendors invests massively for the “Cloud
Consumption” market
• Most customers has a multi-cloud strategy
9. IoT at the “Edge”
• Process massive amount of data with
limited network bandwidth
• Connected Factory/Building/Oil Rig/Device
• Smart & effective Data Collection
• Privacy, Security & Offline support
10. Automated machine
learning (AutoML)
• Automating the process of applying Machine
Learning end-to-end
• Data scientists' skills are hard to automate
• Helps in optimizing algorithm parameters,
Learning, Preprocess and clean data,
Postprocess ML models and more
11. How to get started
• Strong BC with well documented KPI & targets
• Start small, think BIG
• Ensure involvement and governance
• Establish partnership
12. How to get started
You need someone who:
• Owns the Business Problem
• Understands Data, Data Quality & Data Security
• Understands Analytics – Machine Learning,
Statistics, Optimization and Forecasting
• Knows how to put analytics in action by
operationalizing for outcomes
13. Build AI
• Tailor made solutions
• AI components and Cognitive services
• ex. Natural Language Understanding, Text to
Speech, Image/Face Recognition & Personality
Insights
15. Hybrid and On-Prem
Computing
• Enterprise software as pre-packaged
Kubernetes applications
• Build once, run everywhere
• Hybrid cloud that scales and maintain security
16. Opportunities for you
MSPs can use AI to increase their profits:
- Condition-driven automation
- Repetitive task-driven automation
- Look for patterns
- Look to automate across multiple client sites
- Look for event triggers
17. What can we do
together?
• Increase profit with better insight
• End to end project deliveries
• Access to Technology and Competency
18. Whatever journey your organisation is on
to an optimised cloud enabled future,
don't take on the task alone.
Talk to the technology transformation experts at
Crayon and make your ambitions a reality.
Thank You!
www.crayon.com