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Automation can Generate and Scale Content Faster

If one has read quarterly earnings reports, the individual likely has been run into without even realizing it. Associated Press uses NLG to write 4,400 full earnings reports each quarter for the US companies. It also uses NLG to generate recaps for 10,000 MLB-affiliated baseball games each year and preview 5,000 NCAA men’s basketball games. Journalists can spend more time focusing on stories that require human talents, such as in-depth interviews, reporting on breaking news by automating data-driven content. Automating time-consuming, repetitive content at scale allows journalists to craft the perfect article, press release, or blog post instead.  

Distribute Hyper-personalised Content

NLP enables marketers to create a constant flow of customized content. Consumers want to feel brands understand them and their needs, and hyper-personalized, relevant content can build this connection. Most companies, unfortunately, don’t have the resources or time to develop and distribute customized content. Things like email marketing or app notifications are rarely tailored to individual users.  

Streamline Analytics and Reporting

Not everybody is a data expert and can look at an analytics dashboard for establishing the optimal next steps. Even with user-friendly dashboards and visualizations, many people are still not sure how to benefit from data. Additionally, it’s difficult for most communication professionals to tie the activities to ROI. On the reporting side, clients request daily, weekly, and monthly summaries highlighting competitor analyses and campaign successes. Every decision about what goes into these reports can be driven by analytics. Monitoring social analytics, for mentions, brand sentiment, can be time-consuming, monotonous, and templated. Yet, it is necessary to track progress, validate work, and grow a company’s health. NLG enables one to produce reports in seconds, with data updating in real-time. The individual then can distribute them to clients, supervisors, colleagues, and executives in a way they can easily digest and understand.  

Enter NLG-Based Automation

Sports Fantasy Football uses NLG to engage and amuse their massive user base in a highly customized way. They produce more than 70 million personalized draft reports. Previews and recaps delivered directly to fantasy football users in seconds are all done using NLG. It has helped Yahoo adding more than 100 years of incremental audience engagement. This is based on the average number of unique readers per week and the average number of minutes per visit.

Although automation is not new in marketing, many agencies are still in the early stages of collecting data and learning how to use it to drive value through AI automation. A 2023 study found that 49% of the respondents agreed that artificial intelligence (AI) and automation would change their working way. And 31% believed they would already avail the benefits. However, organizations are also dealing with the fear that AI and automation could potentially threaten job losses across several sectors. Advancements in technology will undoubtedly change current roles and create new ones. For example, communicators could soon use natural language generation (NLG) in Storytelling. NLG is a type of AI that turns data into clear, human-sounding narratives. This new technology has the power to generate content at scale, hyper-personalized communication, and optimize analytics reporting, which can lead to better marketing chúng tôi one has read quarterly earnings reports, the individual likely has been run into without even realizing it. Associated Press uses NLG to write 4,400 full earnings reports each quarter for the US companies. It also uses NLG to generate recaps for 10,000 MLB-affiliated baseball games each year and preview 5,000 NCAA men’s basketball games. Journalists can spend more time focusing on stories that require human talents, such as in-depth interviews, reporting on breaking news by automating data-driven content. Automating time-consuming, repetitive content at scale allows journalists to craft the perfect article, press release, or blog post chúng tôi enables marketers to create a constant flow of customized content. Consumers want to feel brands understand them and their needs, and hyper-personalized, relevant content can build this connection. Most companies, unfortunately, don’t have the resources or time to develop and distribute customized content. Things like email marketing or app notifications are rarely tailored to individual chúng tôi everybody is a data expert and can look at an analytics dashboard for establishing the optimal next steps. Even with user-friendly dashboards and visualizations, many people are still not sure how to benefit from data. Additionally, it’s difficult for most communication professionals to tie the activities to ROI. On the reporting side, clients request daily, weekly, and monthly summaries highlighting competitor analyses and campaign successes. Every decision about what goes into these reports can be driven by analytics. Monitoring social analytics, for mentions, brand sentiment, can be time-consuming, monotonous, and templated. Yet, it is necessary to track progress, validate work, and grow a company’s health. NLG enables one to produce reports in seconds, with data updating in real-time. The individual then can distribute them to clients, supervisors, colleagues, and executives in a way they can easily digest and understand.Sports Fantasy Football uses NLG to engage and amuse their massive user base in a highly customized way. They produce more than 70 million personalized draft reports. Previews and recaps delivered directly to fantasy football users in seconds are all done using NLG. It has helped Yahoo adding more than 100 years of incremental audience engagement. This is based on the average number of unique readers per week and the average number of minutes per visit. If one tends to break the noise to deliver hyper-personalized messages to every single audience member, AI automation is an excellent place to start.

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Ai And The 6 Levels Of It Automation

We are moving aggressively into a period of automation across IT services. Yet, the industry has to adopt anything like the automotive industry to talk comparatively about what will eventually be an IT artificial intelligence (AI) hierarchy.  

The danger with any discussion on IT automation is the concern about job losses that can destroy almost any automation effort, because the status of critical decision makers is often connected to the number of people they manage. But with today’s massive shortage of qualified and particularly diverse candidates, the bigger problem, which automation can address with less controversy, is staffing shortages that have become problematic for most firms. 

We aren’t anywhere near full automation yet, which will have staffing implications, but the industry will have years to get there. Since IT is generally understaffed, it will be a while before this effort results in downsizing. But this trend does suggest that retraining be considered as part of any progressive automation process.  

Automotive Levels of Automation

Autonomous cars have six levels.  

Level 0 is where we started, where the driver does everything.  

Level 1 is cruise control, where only the throttle is handled somewhat automatically to avoid hitting the car in front of you. 

Level 3 is where things get interesting, and the driver can give up driving during certain conditions, like stop-and-go traffic or freeways. At Level 3, you can’t relax and have to be ready to assume control at any moment.  

Level 4 can give the car complete control. Still, the driver may occasionally be asked to step in if the car sees a unique problem, like a flooded underpass or an unexpected accident, and needs non-critical help to solve the problem.  

Level 5 is what we generally think of when we talk about autonomous driving. This level is where you don’t even need to be in the car, as it is fully autonomous.  

Autonomous Levels of IT

Using the automotive autonomous levels and a guideline, I’m suggesting the following:  

Level 0 again would be no automation at all. You might get reports and alerts, but someone virtually always has to act on them.  

Level 1 is where you get some basic automation, but the scripts aren’t dynamic. While this level can address some of the repetitive tasks, the overall capability is pretty basic.  

Level 3 uses machine learning AIs much more aggressively, and an increasing number of functions happen automatically with only some oversight. However, should a problem occur, people still need to be on hand to address it, or the system may have to shut down to prevent damage.  

Level 5 is IT in a box. This level is a full deep learning deployment where the system determines what is needed and acts on the problem independently. I doubt we can deliver Level 5 before we get to general-purpose AIs, which aren’t due until late next decade, so we have some time. By this time, much of IT will need to be retrained to do something else, because this would be similar to outsourcing IT. But in this case, you are outsourcing it to an AI, which a third-party vendor in the cloud could provide.  

Wrapping Up: Trust Is Critical

While the market has some Level 3 solutions, adoption is light, and Level 4 and 5 systems aren’t expected to be available for years yet, let alone broadly adopted. 

And IT isn’t the only function being automated. Sales, particularly online and telesales, will be moving to conversational AIs. Accounting is moving aggressively to blockchain and related automated functions. And we are moving toward turning manufacturing plants into big automated 3D printers, some of which will be located at customer sites.  

We are just at the start of digital transformation. What is coming will potentially free us from those tasks we hate, create opportunities that we don’t see, and have significant potential to change operations for good if done right and ill if not. Given how badly most early AI deployments have gone, I doubt many are even moderately ready for what’s coming and deploying AI.  

What Is Marketing Automation And How Is Ai Transforming It?

80% of the top-performing businesses worldwide have witnessed a significant increase in earnings and customer engagement through marketing automation technologies. Eliminating redundancy, accelerating tasks, and promising optimal accuracy– marketing automation is a reliable tactic to thrive in today’s competitive world. In this article, we’ll explore the basics of marketing automation, its benefits, and how AI is transforming it to help businesses create more effective marketing campaigns and drive growth. We’ll also discuss some practical examples of AI-powered marketing automation tools and strategies. Get ready to discover the future of marketing automation!

What is Marketing Automation?

Marketing automation is a program that allows businesses to efficiently target consumers with automated marketing communications using mediums such as emails, websites, social networking sites, and messaging to obtain prospective customers.

Marketing automation solutions allow you to cut down on time, and you get improved outcomes and less human error when repeated activities are automated. You can concentrate on more fundamental duties, such as marketing plan and layout, target building, analysis, branding uniformity, KPI monitoring, and more, rather than doing tedious stuff.

Impact of AI in Marketing Automation

With the emergence of artificial intelligence (AI), marketing automation is undergoing another transformation, enabling marketers to leverage the power of AI to gain deeper insights into their customers and deliver even more targeted and personalized content. Here are a few ways in which AI is impacting Marketing Automation:

Personalization: AI-powered marketing automation can enable businesses to deliver highly personalized content to their customers, based on their preferences, behavior, and demographics.

Predictive analytics: AI algorithms can analyze vast amounts of customer data to identify patterns and predict future behaviors, enabling businesses to make data-driven decisions and optimize their marketing campaigns.

Chatbots: AI-powered chatbots can handle customer queries and interactions, providing 24/7 customer service and freeing up human agents to focus on more complex tasks.

Image and Video Analysis: AI-powered image and video analysis can help businesses understand how their customers are interacting with their content, and optimize it for maximum impact.

Generative AI: The invention of generative AI has opened up new possibilities for marketing automation. It can create unique content, such as product descriptions, headlines, and even entire articles, without human intervention.

Voice Assistants: AI-powered voice assistants can help businesses engage with their customers in new ways, providing personalized recommendations and offers, and creating a seamless customer experience.

Customer Segmentation: AI algorithms can segment customers based on their behavior, preferences, and demographics, enabling businesses to target them with more relevant and personalized content.

Source: Forbes

Why is Marketing Automation Important?

Some of the reasons for marketing automation implementation are as follows:

Both business-to-business (B2B) and business-to-consumer (B2C) companies can utilize marketing automation tools to maintain their marketing communications up to date and reach prospective consumers.

Everything is automatically preserved in your centralized cloud services when you use marketing automation effectively, and organizational procedures can enable you to set task priorities as needed.

How Does Marketing Automation Work?

Marketing automation software works on its prime goal- replacing manual and redundant tasks to save time and effort. It allows marketers to allocate their energy and resources to curating strategies, content, and well-thought problem-solving solutions.

The key steps involved in working marketing automation are:

It then creates a useful database, identifying and segmenting potential customers from its collected data.

Next, it designs campaigns for different segments and incorporates personalized attributes that would hit the target audience right.

It makes campaigns more effective by delivering personalized content on the right channel at the right time, which is otherwise too cumbersome, given the vast range of digital marketing platforms.

Lastly, it analyzes the performance to figure out what’s working and what’s not. It adjusts as needed and sets out to drive greater marketing ROI.

Key Features of Marketing Automation Software

Eliminates every task that feels like chores

Helps plan campaigns from a single spot

Provides detailed customer histories

Automatically cleans up duplicate records

End-to-end email campaign functionality

Social media integration to track and analyze customers’ social presence

Real-time automatic alerts for internal team members or to other teams

Easy workflow creation and management

Real-time responses for customers

Customizable email and newsletter templates

Examples of Marketing Automation Software 

HubSpot Marketing Automation

ManyChat

Moosend

Snov.io

Omnisend

EngageBay

Ontraport

SendinBlue

ActiveCampaign

Benefits of Marketing Automation

With access to a range of options for marketing automation, it is crucial to understand the best practices to explore the potential of the technology to its fullest.

1. Building a solid foundation with a CRM system

Customer Relationship Management (CRM) system brings many benefits, including the ability to precisely segment customers, strategically plan sales activities, monitor sales, boost customer service, and streamline processes. With all customer data centralized within the CRM, you can utilize the best benefits when integrating it with marketing automation.

2. Defining buyer personas and customer journeys

Buyer personas or imaginary profiles of your typical customer base help ensure that you reach your target audience. Buyer personas assist in analyzing customers’ demographics, requirements, challenges, and interests. You must know your target audience’s customer journeys. What questions are they putting up, the avenues they use for information, and what decision stages do they lie in? With answers to these, you can map out a workflow that offers value to the right audience at the right time.

3. Creating targeted and personalized content

With so much information readily available and flooding inboxes with sales content, creating engaging content that strikes the cords right is necessary. Cut through the heaps with targeted content. It could be blogs, videos, polls, webinars, quizzes, live streams, social media posts, etc.

4. Continuously testing and optimizing campaigns

All marketing efforts go in vain when not monitored precisely. With automated analysis, seek the slightest opportunity to optimize your campaigns and include points that add user value. Do not shy from testing innovative ideas. However, ensure that you keenly analyze its impact and make amends as and when required.

5. Aligning sales and marketing teams Choosing the Right Marketing Automation Software

With a range of platforms offering competitive features, picking the most suitable is often confusing. Here are some important factors to consider when selecting a marketing automation platform:

1. User interface

The look of the platform impacts how you use it. A user-friendly interface makes it easy for your team to understand and use the software. You must look for a clear interface with no steep learning curve. Consider taking a demo or a free trial to explore features/ functions.

2. Features and integrations

Every business has its unique requirements. Therefore, you must consider the features and integrations of the platform. Test the offerings, even the ones you would not require. This additional step often opens doors to new ideas and helps businesses flourish.

3. Customer support

Dedicated customer support will make your journey easier. When learning how to use a marketing automation tool or introducing it to your team, having technical support is of great help. So, consider tools that offer the type of support you want— phone, email, and live chat. Also, ask the software provider about their response times and other resources they provide for issue resolution.

4. Pricing

Consider the features you require and how they associate with the pricing. Pricing should be an important factor but not the ultimate deciding factor. Ask the software provider about the platform’s scalability if your business witnesses a change in size. It is best to choose tools that come with transparency about their pricing.

5. Setup and onboarding

Setting up new software can be challenging. Look out for the level of assistance from the provider. Feel free to ask about the kind of setup and onboarding support and the charges (if any). You must also consider enquiring if they offer assistance remotely or in person.

Weigh the pros and cons of each tool before making a choice. Some common pros and cons that you must look for are covered below:

How to Implement Marketing Automation?

Pick a simple tool: Begin with an easy-to-use tool with an intuitive interface, chatbots, and quick issue-resolution support.

Combine it with your website: The first step after choosing a tool is to install a bit of code on your website header.

Start with basics: You can begin marketing automation by sending thank you emails to anyone filling out a form on your website.

Automate data segmentation: When collecting data from your website, set prerequisites to segment it. For instance, a person filling out a form can be marked as a potential or qualified lead. You can also mark out which pages they are interested in by keeping tabs on the specific page they visit. 

Personalize automation: Based on lead activity, you can set up automated messages to reach the audience at the right time.

Strategies for Overcoming Resistance to Change

Listen to their concern with an approach to understanding, not contradicting. Your employee’s thoughts and suggestions will prove valuable in steering your change project.

Communicate the reason for change while highlighting the ease of work via automation.

Make it about employees rather than talking about how it would benefit the company.

Opt for the ripple effect. You can begin by training team members who are natural leaders so that they act as role models for the rest of your employees.

Give demos and show them the data. Let your employees see for themselves and acknowledge the need for the switch.

Tips for Smooth Implementation of Marketing Automation Softwares

Track and review customer behavior across multiple touchpoints in their buying journey.

Identity what are your customers’ motivations, preferences, anticipations, and challenges to engage on a more personalized level.

Create automated messaging workflows that power marketing campaigns.

Develop a segmentation strategy and create unique customer segments.

Leverage the power of automated SMS marketing to send timely reminders of offers, abandoned carts, subscriptions, and more.

Gather customer feedback via marketing automation tools and identify areas of improvement.

Opt for conversational marketing via AI to improve customer engagement and reduce wait time.

Acknowledge the difference between personalization and regular bulk messaging. Addressing the user’s concerns can offer a more meaningful interaction and lead them toward conversion. Consider buying behavior, geolocation, purchase history, name, and other details to suit your customers’ preferences.

Below is a list of leading marketing automation softwares and the benefits of using them:

1. ActiveCampaign

This marketing automation tool offers email marketing, unlimited sending, chat and email support, CRM integration, contact and lead scoring, custom branded forms, and landing pages. You can access custom reporting and a dedicated account representative through their Enterprise plan.

2. GetResponse

It is a popular tool for automated marketing. It helps you create personalized automation workflows that engage and guide potential customers on each step of their conversion journey. It offers a 30-day free trial and demo with custom solutions for clients. You can use the tool to create automation events based on users’ behavior and take actions based on selected conditions. Its filters offer more precise targeting for an enriched experience. 

3. Klaviyo 

With exceptional email deliverability reporting, this growth marketing platform helps deliver more personalized experiences through various marketing channels such as email, SMS, web, and in-app notifications. 

4. Hubspot Marketing Hub  

An extremely easy-to-use marketing automation platform that includes tools for landing page creation, email marketing, social media marketing, analytics and reporting, content management, as well as search engine optimization (SEO).

5. Adobe Marketo Engage 6. Acoustic Campaign

Formerly known as IBM Watson Campaign Automation, this cross-channel, digital marketing platform provides marketers with immense power as they automate emails, social media, and lead management processes. The pricing details of this tool are available on contact. 

7. MailChimp 

This email marketing solution allows you to convert visitors into customers. Understanding that most consumers today spend their time on mobile phones, the tool optimizes emails and landing pages for smartphones. It also allows you to experiment with different campaigns and curate mindful strategies. 

8. EngageBay

A marketing automation platform ideal for small to medium-sized businesses. It helps businesses with email marketing, website chat, and social media management. EngageBay offers drag-and-drop builders for emails and landing pages, SMS marketing, abandoned cart retrieval, quick reminders, push notifications, and autoresponders.

9. Ontraport

It is specifically designed for entrepreneurs and small businesses. It offers CRM and marketing automation, email marketing, landing pages, and e-commerce. Its insightful reporting and analytics give users a clear understanding of their campaigns’ performances.

10. Salesforce Marketing Cloud Account Engagement

This popular cloud platform helps align marketing and sales from a single point. Its data-driven reports, predictive analytics, and many marketing automation features make it one of the most reliable tools in the market. 

If you are looking for a marketing automation software for emails then read our blog on top 10 AI email marketing tools to use in 2023!

Wrapping Up

In a world of digitalization, there are several opportunities to tap into and lure customer attention. Marketing automation can be one of the smartest moves for your business when employed strategically. After all, why spend your time and energy on redundant tasks that can be dealt with far more efficiently by AI?

If you are a business owner, opt for marketing automation and watch how it drives revenue, increases retention, and integrates with all your platforms.

This is it for this article. But before you go, I’d highly recommend you check out our value-loaded workshops like ‘Mastering LLMs: Training, Fine-tuning, and Best Practices‘, ‘Exploring Generative AI with Diffusion Models‘ and ‘Solving Real World Problems Using Reinforcement Learning’ and many more at the DataHack Summit 2023 to level up your data game! Our workshops are your ticket to unlocking immense value, equipping you with practical skills and real-world knowledge that you can apply right away. Picture yourself diving into hands-on experiences, gaining the confidence to conquer any data challenge that comes your way. This is your golden opportunity to enhance your expertise, connect with industry leaders, and open doors to exciting new career opportunities. Don’t wait any longer! Secure your spot and register now for the highly anticipated DataHack Summit 2023.

Related

How Can Cookies Be A Threat?

The Internet is unquestionably the finest source of information regarding items, stores, customer complaints, user experiences, and so on. Companies employ cookies to try to pique users’ interest in browsing and give the best experience possible.

Lon Montulli is credited with inventing cookies in 1995 for the Netscape Communication Corporation.

The term “cookies” comes from the programming phrase “magic that a website may get.

This one-of-a-kind variable is used to differentiate between various users who are attempting to access the system.

Only the website that originally set the cookie may retrieve it.

Some cookies additionally include unique session identifiers and a time value.

Why Do Cookies Exist?

A cookie is a very small text file that stores the current state on the user’s computer. This information may be obtained by the website to determine the current condition of the website. A website can deduce that the user has already visited by glancing at the cookie’s ID field.

A website’s hit count is determined by the unique id assigned to each user. A website may, therefore, uniquely identify the number of visits by utilizing cookies.

Cookies may also be used to classify repeat users and track how many times a single person sees the page.

Cookies can record preferences and settings, and this information can be used to recall user choices and create customised experiences for specific users. When it comes to e-commerce sites, the unique ID can be utilised to create a user’s shopping cart. A user can add things to a shopping cart, and this preference, together with the unique id, is saved in the site’s database. When the same user returns to the site, the unique id from the cookie may be utilised to obtain that user’s buying preferences.

Cookies are also used by websites to measure how much time a user spends on the site and which links the user hits. Furthermore, Cookies can also be used to remember a user’s personal preferences and colour settings.

How Does YouTube Use Cookies

Consider the case of YouTube, which is owned by Google. YouTube utilises cookies to assess user preferences and personalize user results based on that information.

When a person first views YouTube, he or she will be presented with a random number of results.

After one or two views, the user establishes a preference, which is saved in the user’s cookies.

When the same user logs in again, YouTube might utilise this cookie to find videos that are similar to the user’s preferences.

How to Securely Manage Cookies and Browse

Given the nature of cookies and their possible privacy implications, it’s crucial to think about how they affect your personal security. As a result, warnings) and keep your browser up to date. You might be subject to malicious attacks if you use an older version. As a result, it’s a good idea to update your browser on a frequent basis to ensure that all security updates are installed.

Risks Associated with Cookies

Following are some of the examples in which the attackers use cookies to carry out an attack −

Cross-site Request Forgery (XSRF) Attack

Fixation of the Session

Site-to-site Scripting

Cookie Tossing Attack

Cookie Overflow Attack

Cross-site Request Forgery (XSRF) Attack

A cookie is sent by a browser in response to a request, independent of the source of the request. This is where the real issue with cookies arises. When a website gets a request, it is unable to determine whether or not for the cookie when it gets the request. It then looks for John’s cookie, interprets it as a legitimate request, and deletes it.

Fixation of the Session

Attacks on session fixation are based on the application level. An attacker forces the victim to use the attacker’s or another’s session ID in this sort of attack. This is accomplished by exploiting the cookie’s browser directive route, which allows the user to impersonate someone else. An attacker can use this strategy to persuade the user to log in as the attacker on several application levels.

Site-to-site Scripting

An attacker must embed the vulnerability in a cookie to carry out a crosssite scripting attack. The exploit vector will then get the payload from the cookie and carry out the exploitation. This type of assault gets more difficult if the cookie has already been established. In this situation, the attacker must first get controlof the first cookie in the cookie string before launching the assault.

Cookie Tossing Attack

Cookie throwing is one of the most common sorts of cookie attacks, and it visits the same site.

The issue now is that the cookie has no path or website name. As a result, if an attacker creates a subdomain cookie and transmits it along with a real cookie, the webserver will accept both.

Due to the absence of a rule requiring the browser to transmit the domain cookie first, it may send the subdomain cookie first.

If the malicious subdomain cookie is the first one received by the web server, it will be treated as genuine, and the value of that cookie will be used to give the user a session.

The web server cannot determine whether a cookie is real since cookie properties such as domain path secure and Http Only are not supplied to it.

Cookie Overflow Attack

A parent domain cookie can be changed with a subdomain cookie in this sort of attack by employing a Jscript in the subdomain.

Browsers have a restriction on how many cookies they may keep, and some, such as Chrome, don’t check if the cookies are from a domain or a subdomain. It does nothing but save the cookies that are supplied to it.

The subdomain cookies that will be updated will not be of the HttpOnly or secure types.

After saving the subdomain cookie, an attacker can modify the cookie’s expiration date, rendering the cookie meaningless.

Now the attacker has the ability to create a new malicious cookie and send it to the webserver.

Furthermore, there is no way for a web server to tell if a cookie is secure or HttpOnly. As a result, manufactured cookies can be used to carry out an attack.

Conclusion

To conclude, stay away from dubious websites (pay attention to any browser warnings) and keep your browser up to date. You might be subject to malicious attacks if you use an older version. As a result, it’s a good idea to update your browser frequently to ensure that all security updates are installed.

How Automation And Analytics Work Together

How can automation and analytics drive digital transformation?

As the CTO of GE Digital, Colin Parris – formerly a VP at IBM for a decade – is actively involved with shaping how automation and analytics drive business productivity and digital transformation. This includes: 

How businesses increase output at lower costs.

How lean business transformation helps customers get to value faster.

How technology can support customers in light of COVID-19.

Please join this wide-ranging discussion with Colin Parris, a key thought leader in transforming business.

Download the podcast:

“I think we’re seeing two things change. One is this notion of acceleration. These firms are seeing that they need to accelerate it and they can. And the second is this thing I would call normalization. [Digital transformation] is now becoming part of the fabric and accepted.”

“I remember having a discussion with the CEO of NYPA in which he was saying he had discussed with his team, ‘How long will it take for us to go and do remote operations?’ They said that transformation would take three to four, maybe five years. They did it in five days because of COVID, because they had to.”

“With any kind of digital transformation, companies are looking for two things. They were looking for productivity, and they were looking to manage the market dynamics. In terms of productivity, they always have the view that software and automation can actually give them more capability.”

“The second thing they’re saying is that in terms of handling market dynamics, they always knew they have to plan long term. Now, with COVID, you have to think short term. You have to think doing it right now, right away.”

“One other quick example, Haverhill, a water utility in Massachusetts. We have a control system working with them. We’ve been working with them for years on actually remote monitoring. When you tie that to the automation system, they control something like 5 million gallons of water annually. They were able to move from a control system where you can have one person off-site running this control system for this entire 58-59 thousand homes. Again, COVID is actually proving these things out. A powerful way to accelerate it and make technology the new normal.”

“We, as engineers, are custom-building models. We build a model, and we use the model to design something. A model is a way you think something works. And then we use that to design, we build a model to understand what the problem looks like, and we use that to figure out problems. We all use models.”

“What a twin is, it’s a model, but it has two different characteristics. It’s a living learning model. In other words, after I finish to use the model and design, I throw it away because I built the thing. How about if you keep that model alive or parts of it and then constantly feed it real-time data so the model changes to reflect the asset as it’s being used right now in the world? So it’s a living model. We have something like 1.2 million of these twins built.”

“Let me use a utility example, CPV, Competitive Power Ventures. And what they are using their twin to do, first of all, is to predict. Then they use the same twin to optimize.”

“So now we have something, a twin controlling how high can I turn up the temperature so I could heat it up to get more electricity while not damaging the asset? So a twin, we have one example of doing both, prediction and optimization.”

“Initially, to form the digital twin, you need the expertise. But once you have a twin, the model, you can deploy the model and then that model then communicates with regular humans who use it.”

“So I’ve found a way to deliver value through the twins. I can tell you how to save money, or a how to gain revenue in a variety of ways. Now the problem is, every time we build these things, how do you actually deploy it?”

“You’ll say, ‘What about business risk?’ “Collin, I don’t trust this model. This is a model, a neuro network, a black box. I don’t trust it.” How should I think about that? Okay, so what we began working on a couple of years ago with something called Humble AI.”

“So what Humble AI does is that it knows what is the zone in which I’m competent. Ah, seven to eight I’m competent, that’s my zone of competency. Outside the zone of competency, I use the regular models you had before. Then I ask for help. Then I say, ‘Can I get more data about, data in the 12 mile per hour region?’ So this is Humble AI.”

“So what we have now is we have an AI system that can take that information before it gets there. We can get to that information off the turbine, and create the graph. And say, ‘Well, given that graph and comparing it to what the designers have written in the manual, this is a pitch problem.’ That person then will ask, ‘Why do I believe that?’ You pull out of the manual, ‘Here’s the exact graph I compared it against to know why it was exactly going to be a pitch problem.’ And so now the human says ‘Alright, that is okay, I have seen this in my manual before, I think it’s right.’ This is Explainable AI.”

“What if two wind turbines could talk or the wind turbines in one big farm could talk to each other and one wind turbine could say, ‘I am actually feeling this funny vibration, has any of you ever felt it before?’ And one of them could say, “I felt it before, this was the problem then.”

“You can have the wind turbines communicating and answering their own questions and then telling it to us. So we have been developing something called an Emergent Language. It’s a new form of AI in which we are looking at the way data comes off and getting wind turbines to talk to each other, to have a language in which they can ask each other questions and we’ve had some amazing results.”

“Oh, no. There are two things we do it for. One we do it for safety. Because if there are things that are about to happen, we have challenges.”

“The next thing that will happen is that nothing stays the same. There gonna be other new problems that show up, I can have the humans focusing on the new problems. What I don’t want is my best people focusing on problems we’ve solved, but you just didn’t know you solved them before.”

“So I don’t see loss of jobs, especially as there are more and more wind farms that are growing. I see humans working at what they do best and not having to do that work in which it’s dirty or dangerous or dull.”

Ai Can Change The Future Of Seo

The Big Picture

We state”search engines,” but the majority of the time, we are talking about Google. Bing, Yahoo!, DuckDuckGo, along with other motors just share a small percent of the research user base, and also the majority of these systems are modeled following Google’s in the first location. Our big issue is, how is Google going to integrate AI from the future to alter how search functions for the typical user?

Historically, Google has updated its algorithms with two primary goals in mind:

Improve user experience. Google requires users to find the answers they’re looking for, and receive accurate, valuable content. This is a necessary category, and a complicated one; to achieve this, Google not only has to perfect how its search engine functions, but also how it finds, organizes and evaluates the quality of content on the web.

Keep users on Google. Google makes money when people use it, and stay on the platform as long as possible. We’ll see why that’s important in a future section.

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RankBrain and Machine Learning

Google is currently using machine learning in a couple of various ways, and it is merely a matter of time until it progresses.

To begin with, let us contemplate RankBrain, a system learning-based update to Google’s Hummingbird algorithm, which started in 2024. The Hummingbird upgrade, from 2013, initially rolled out”semantic search” capabilities. It was made to rate the context of consumer inquiries, instead of the specific contents; instead of assigning precise match keywords, Hummingbird enabled Google to consider synonyms, related phrases, and much more. This is a step in the ideal direction since it intended users could find far better outcomes, and search optimizers could no longer eliminate keyword stuffing.

RankBrain has been a modification that allowed Google to study enormous amounts of user search information and mechanically enhance its interpretation of consumer phrases. It had been mostly concentrated on lengthy, convoluted, or hard-to-understand phrases, finally reducing them down to some length and simplicity amount the algorithm could easily manage. It has been self-updating and improving ever since.

Content Quality and Link Quality

I guess we will also see important AI improvements applied to understand the essence of the links and content made by internet search optimizers.

Links and articles will be the focal points of all SEO strategies. Google research links to figure domain name – and page-level jurisdiction (or trustworthiness); normally, the more links a website has pointed into it, and the greater people links are, the greater it is likely to rank. In the same way, better-written, more pertinent content will rise in SERP positions –and allure to internet users. Better articles and better connections mean you are going to wind up getting a greater return on investment (ROI) to your search engine optimization plan .

Through time, Google has gotten better in assessing the standard of links and content from sites; research marketers have developed from attempting to deceive Google’s algorithm to just hoping to make their best possible work.

At this time, Google’s strategies for assessing the abstract”quality” of links and content are great –they may always be improved. It would be simpler for an AI representative to slowly learn what makes great content”great,” compared to rely upon a manual broker programming these parameters into a system. I think Google will make more attempts to automate quality test in the not too distant future.

Individualization

Google has also put a lot of effort to differentiate its search results. If you search for the same phrase in Phoenix, Arizona and Cleveland, Ohio, you are probably going to get fundamentally different results. You may also get different results based on your search history, and even demographic information Google “knows” about you.

Right now, these personalization efforts are impressive but limited. We are not surprised that Google knows where we are, or the last few things we have discovered. But in the near future, Google may be able to use Artificial Intelligence to make more in-depth forecasts. Based on your historical searches and search data from millions of other users like you, Google may be able to recommend search or search results to you before you know they need them.

For search marketers, this is both an opportunity and a threat. If you are able to capitalize on predictive searches, you can get a huge edge over the competition – but then, if Google’s algorithm methods are opaque, you may have a harder time understanding when and how your results are available to users. appear to.

Smart Results

Real Time Changes and Adaptability

AI is unusually good at analyzing huge amounts of information, and much faster than even an expert human group. Historically, Google has generated periodic updates into its own algorithm with important, game-changing algorithm fluctuations dropped every couple of months. But lately, those algorithm upgrades have cut off in favour of smaller, far more regular updates.

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Content Production and Onsite Optimization

Additionally, it is worth noting that AI will not only be exploited by Google and other search engines. We will also observe the development and usefulness of AI on behalf of search marketers. AI-based content generators are getting more sophisticated and more prevalent; finally, search marketers might have the ability to use these to create and distribute content well enough to”fool” Google’s algorithms. From that point, this will probably become an arms race involving search marketers and lookup algorithms–not too unlike what we currently have.

What’s more, smart onsite optimization engines may significantly simplify the technical attempts that search marketers now must make. Present-day plugins and onsite search engine optimization tools are useful but incomplete; at the not too distant future, AI and machine learning can create these considerably more capable.

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