Archive for the ‘Artificial Intelligence’ Category

Will Artificial Intelligence Kill College Writing? – The Chronicle of Higher Education

When I was a kid, my favorite poem was Shel Silversteins The Homework Machine, which summed up my childhood fantasy: a machine that could do my homework at the press of a button. Decades later that technology, the innocuously titled GPT-3, has arrived. It threatens many aspects of university education above all, college writing.

The web-based GPT-3 software program, which was developed by an Elon Musk-backed nonprofit called OpenAI, is a kind of omniscient Siri or Alexa that can turn any prompt into prose. You type in a query say, a list of ingredients (what can I make with eggs, garlic, mushrooms, butter, and feta cheese?) or a genre and prompt (write an inspiring TED Talk on the ways in which authentic leaders can change the world) and GPT-3 spits out a written response. These outputs can be astonishingly specific and tailored. When asked to write a song protesting inhumane treatment of animals in the style of Bob Dylan, the program clearly draws on themes from Dylans Blowin in the Wind:

How many more creatures must suffer?How many more must die?Before we open up our eyesAnd see the harm were causing?

When asked to treat the same issue in the style of Shakespeare, it produces stanzas of iambic tetrameter in appropriately archaic English:

By all the gods that guide this EarthBy all the stars that fill the skyI swear to end this wretched dearthThis blight of blood and butchery.

GPT-3 can write essays, op-eds, Tweets, jokes (admittedly just dad jokes for now), dialogue, advertisements, text messages, and restaurant reviews, to give just a few examples. Each time you click the submit button, the machine learning algorithm pulls from the wisdom of the entire internet and generates a unique output, so that no two end products are the same.

The quality of GPT-3s writing is often striking. I asked the AI to discuss how free speech threatens a dictatorship, by drawing on free speech battles in China and Russia and how these relate to the First Amendment of the U.S. Constitution. The resulting text begins, Free speech is vital to the success of any democracy, but it can also be a thorn in the side of autocrats who seek to control the flow of information and quash dissent. Impressive.

From an essay written by the GPT-3 software program

The current iteration of GPT-3 has its quirks and limitations, to be sure. Most notably, it will write absolutely anything. It will generate a full essay on how George Washington invented the internet or an eerily informed response to 10 steps a serial killer can take to get away with murder. In addition, it stumbles over complex writing tasks. It cannot craft a novel or even a decent short story. Its attempts at scholarly writing I asked it to generate an article on social-role theory and negotiation outcomes are laughable. But how long before the capability is there? Six months ago, GPT-3 struggled with rudimentary queries, and today it can write a reasonable blog post discussing ways an employee can get a promotion from a reluctant boss.

Since the output of every inquiry is original, GPT-3s products cannot be detected by anti-plagiarism software. Anyone can create an account for GPT-3. Each inquiry comes at a cost, but its usually less than a penny and the turnaround is instantaneous. Hiring someone to write a college-level essay, in contrast, currently costs $15 to $35 per page. The near-free price point of GPT-3 is likely to entice many students who would otherwise be priced out of essay-writing services.

It wont be long before GPT-3, and the inevitable copycats, infiltrate the university. The technology is just too good and too cheap not to make its way into the hands of students who would prefer not to spend an evening perfecting the essay I routinely assign on the leadership style of Elon Musk. Ironic that he has bankrolled the technology that makes this evasion possible.

To help me think through what the collision of AI and higher ed might entail, I naturally asked GPT-3 to write an op-ed exploring the ramifications of GPT-3 threatening the integrity of college essays. GPT-3 noted, with mechanical unself-consciousness, that it threatened to undermine the value of a college education. If anyone can produce a high-quality essay using an AI system, it continued, then whats the point of spending four years (and often a lot of money) getting a degree? College degrees would become little more than pieces of paper if they can be easily replicated by machines.

The effects on college students themselves, the algorithm wrote, would be mixed: On the positive side, students would be able to focus on other aspects of their studies and would not have to spend time worrying about writing essays. On the negative side, however, they will not be able to communicate effectively and will have trouble in their future careers. Here GPT-3 may actually be understating the threat to writing: Given the rapid development of AI, what percent of college freshmen today will have jobs that require writing at all by the time they graduate? Some who would once have pursued writing-focused careers will find themselves instead managing the inputs and outputs of AI. And once AI can automate that, even those employees may become redundant. In this new world, the argument for writing as a practical necessity looks decidedly weaker. Even business schools may soon take a liberal-arts approach, framing writing not as career prep but as the foundation of a rich and meaningful life.

So what is a college professor to do? I put the question to GPT-3, which acknowledged that there is no easy answer to this question. Still, I think we can take some sensible measures to reduce the use of GPT-3 or at least push back the clock on its adoption by students. Professors can require students to draw on in-class material in their essays, and to revise their work in response to instructor feedback. We can insist that students cite their sources fully and accurately (something that GPT-3 currently cant do well). We can ask students to produce work in forms that AI cannot (yet) effectively create, such as podcasts, PowerPoints, and verbal presentations. And we can design writing prompts that GPT-3 wont be able to effectively address, such as those that focus on local or university-specific challenges that are not widely discussed online. If necessary, we could even require students to write assignments in an offline, proctored computer lab.

Eventually, we might enter the if you cant beat em, join em phase, in which professors ask students to use AI as a tool and assess their ability to analyze and improve the output. (I am currently experimenting with a minor assignment along these lines.) A recent project on Beethovens 10th symphony suggests how such projects might work. When he died, Beethoven had composed only 5 percent of his 10th symphony. A handful of Beethoven scholars fed the short, completed section into an AI that generated thousands of potential versions of the rest of the symphony. The scholars then sifted through the AI-generated material, identified the best parts, and pieced them together to create a complete symphony. To my somewhat limited ear, it sounds just like Beethoven.

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Will Artificial Intelligence Kill College Writing? - The Chronicle of Higher Education

University of Washington graduates use artificial intelligence to create new proteins – NBC Right Now

SEATTLE, Wash.-

For over two years, protein structure prediction has been changed by machine learning. On Sept. 15, two science related research talk about a similar idea in the revolution of protein design.

The findings show how machine learning can create protein molecules that are more accurate and made quicker than before.

With these new software tools, we should be able to find solutions to long-standing challenges in medicine, energy, and technology, said senior author David Baker, professor of biochemistry at the University of Washington School of Medicine.

The algorithm used in machine learning which includes RoseTTAFold have been trained to predict the smaller detailed shapes if natural proteins based on their amino acid sequences.

Machine learning is a type of artificial intelligence that allows computers to learn from data without having to be programmed.

A.I. has the ability to generate protein in two ways. One being akin to DALL-E or other A.I. tools that produce an output from simple prompts. The second is the autocomplete feature we can find in a search bar.

As a way of making things go by faster the A.I. team created a new algorithm that creates amino acid sequences. This tool, called ProteinMPNN, creates the sequence in one second. That's over 200 minutes faster than previous best software.

The Baker Lab also says combining new machine learning tools could reliably generate new proteins that functioned in the laboratory. Among those were the nanoscale ring that could make up part of a custom nanomachines.

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University of Washington graduates use artificial intelligence to create new proteins - NBC Right Now

Insights on the Artificial Intelligence Global Market to 2030 – Featuring Baidu, Clarifai and Google Among Others – PR Newswire

DUBLIN, Sept. 14, 2022 /PRNewswire/ --The "Artificial Intelligence Market Size, Share & Trends Analysis Report by Solution, by Technology (Deep Learning, Machine Learning, Natural Language Processing, Machine Vision), by End Use, by Region, and Segment Forecasts, 2022-2030" report has been added to ResearchAndMarkets.com's offering.

The global artificial intelligence market size is expected to reach USD 1,811.8 billion by 2030. The market is anticipated to expand at a CAGR of 38.1% from 2022 to 2030.

Artificial Intelligence (AI) denotes the concept and development of computing systems capable of performing tasks customarily requiring human assistance, such as decision-making, speech recognition, visual perception, and language translation. AI uses algorithms to understand human speech, visually recognize objects, and process information. These algorithms are used for data processing, calculation, and automated reasoning.

Artificial intelligence researchers continuously improve algorithms for various aspects, as conventional algorithms have drawbacks regarding accuracy and efficiency. These advancements have led manufacturers and technology developers to focus on developing standard algorithms. Recently, several developments have been carried out for enhancing artificial intelligence algorithms. For instance, in May 2020, International Business Machines Corporation announced a wide range of new AI-powered services and capabilities, namely IBM Watson AIOps, for enterprise automation. These services are designed to help automate the IT infrastructures and make them more resilient and cost reduction.

Various companies are implementing AI-based solutions such as RPA (Robotic Process Automation) to enhance the process workflows to handle and automate repetitive tasks. AI-based solutions are also being coupled with the IoT (Internet of Things) to provide robust results for various business processes. For Instance, Microsoft announced to invest USD 1 billion in OpenAI, a San Francisco-based company. The two businesses teamed up to create AI supercomputing technology on Microsoft's Azure cloud.

The COVID-19 pandemic has emerged as an opportunity for AI-enabled computer systems to fight against the epidemic as several tech companies are working on preventing, mitigating, and containing the virus. For instance, LeewayHertz, a U.S.-based custom software development company, offers technology solutions using AI tools and techniques, including the Face Mask Detection System to identify individuals without a mask and the Human Presence System to monitor patients remotely. Besides, Voxel51 Inc., a U.S.-based artificial intelligence start-up, has developed Voxel51 PDI (Physical Distancing Index) to measure the impact of the global pandemic on social behavior across the world.

AI-powered computer platforms or solutions are being used to fight against COVID - 19 in numerous applications, such as early alerts, tracking and prediction, data dashboards, diagnosis and prognosis, treatments and cures, and maintaining social control. Data dashboards that can visualize the pandemic have emerged with the need for coronavirus tracking and prediction. For instance, Microsoft Corporation's Bing's AI tracker gives a global overview of the pandemic's current statistics.

Artificial Intelligence Market Report Highlights

Key Topics Covered:

Chapter 1 Methodology and Scope

Chapter 2 Executive Summary

Chapter 3 Market Variables, Trends & Scope3.1 Market Trends & Outlook3.2 Market Segmentation & Scope3.3 Artificial Intelligence Size and Growth Prospects3.4 Artificial Intelligence-Value Chain Analysis3.5 Artificial Intelligence Market Dynamics3.5.1 Market Drivers3.5.1.1 Economical parallel processing set-up3.5.1.2 Potential R&D in artificial intelligence systems3.5.1.3 Big data fueling AI and Machine Learning profoundly3.5.1.4 Increasing Cross-Industry Partnerships and Collaborations3.5.1.5 AI to counter unmet clinical demand3.5.2 Market Restraint3.5.2.1 Vast demonstrative data requirement3.6 Penetration & Growth Prospect Mapping3.7 Industry Analysis-Porter's3.7.1 Supplier Power3.7.2 Buyer Power3.7.3 Substitution Threat3.7.4 Threat From New Entrant3.7.5 Competitive Rivalry3.8 Company Market Share Analysis, 20213.9 Artificial Intelligence-PEST Analysis3.9.1 Political3.9.2 Economic3.9.3 Social3.9.4 Technology3.10 Artificial Intelligence-COVID-19 Impact Analysis

Chapter 4 Artificial Intelligence Market: Solution Estimates & Trend Analysis4.1 Artificial Intelligence Market: Solution Movement Analysis4.1.1 Hardware4.1.1.1. Hardware Artificial Intelligence Market, by Region, 2017-20304.1.1.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)4.1.2 Software4.1.2.1. Software Artificial Intelligence Market, by Region, 2017-20304.1.2.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)4.1.3 Services4.1.3.1. Services Artificial Intelligence Market, by Region, 2017-20304.1.3.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)

Chapter 5 Artificial Intelligence Market: Technology Estimates & Trend Analysis5.1 Artificial Intelligence Market: Technology Movement Analysis5.1.1 Deep Learning5.1.1.1. Deep Learning Artificial Intelligence System Market, by Region, 2017-20305.1.1.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)5.1.2 Machine Learning5.1.2.1. Machine Learning Artificial Intelligence System Market, by Region, 2017-20305.1.2.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)5.1.3 Nlp5.1.3.1. Nlp Artificial Intelligence System Market, by Region, 2017-20305.1.3.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)5.1.4 Machine Vision 5.1.4.1. Machine Vision Artificial Intelligence System Market, by Region, 2017-20305.1.4.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)

Chapter 6 Artificial Intelligence Market: End-Use Estimates & Trend Analysis6.1 Artificial Intelligence Market: End-Use Movement Analysis6.2 Artificial Intelligence Market: End-Use Trends6.2.1 Healthcare6.2.1.1. Healthcare Artificial Intelligence Market, by Region, 2017-20306.2.1.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.1.2. Healthcare by Use Case6.2.1.2.1. Global Ai Healthcare Market, by Use Case, 2017-2030 (USD Billion)6.2.2 Bfsi6.2.2.1. Bfsi Artificial Intelligence Market, by Region, 2017-20306.2.2.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.2.2. Bfsi by End Use6.2.2.2.1. Global Ai Bfsi Market, by End Use, 2017-2030 (USD Billion)6.2.3 Law6.2.3.1. Law Artificial Intelligence Market, by Region, 2017-20306.2.3.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.4 Retail6.2.4.1. Retail Artificial Intelligence Market, by Region, 2017-20306.2.4.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.5 Advertising & Media6.2.5.1. Advertising & Media Artificial Intelligence Market, by Region, 2017-20306.2.5.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.6 Automotive & Transportation6.2.6.1. Automotive & Transportation Artificial Intelligence Market, by Region, 2017-20306.2.6.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.7 Agriculture6.2.7.1. Agriculture Artificial Intelligence Market, by Region, 2017-20306.2.7.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.8 Manufacturing6.2.8.1. Manufacturing Artificial Intelligence Market, by Region, 2017-20306.2.8.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.9 Others6.2.9.1. Others Artificial Intelligence Market, by Region, 2017-20306.2.9.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)

Chapter 7 Artificial Intelligence Market: Regional Estimates & Trend Analysis

Chapter 8 Competitive Landscape8.1 Company Profiles8.1.1 Advanced Micro Devices8.1.1.1 Company overview8.1.1.2 Financial performance8.1.1.3 Product benchmarking8.1.1.4 Strategic Initiatives8.1.2 AiCure8.1.2.1 Company overview8.1.2.2 Product benchmarking8.1.2.3 Strategic Initiatives8.1.3 Arm Limited8.1.3.1 Company overview8.1.3.2 Product benchmarking8.1.3.3 Strategic Initiatives8.1.4 Atomwise, Inc.8.1.4.1 Company overview8.1.4.2 Product benchmarking8.1.4.3 Strategic Initiatives8.1.5 Ayasdi AI LLC8.1.5.1 Company overview8.1.5.2 Product benchmarking8.1.5.3 Strategic Initiatives8.1.6 Baidu, Inc.8.1.6.1 Company overview8.1.6.2 Financial performance8.1.6.3 Product benchmarking8.1.6.4 Strategic Initiatives8.1.7 Clarifai, Inc8.1.7.1 Company overview8.1.7.2 Product benchmarking8.1.7.3 Strategic Initiatives8.1.8 Cyrcadia Health8.1.8.1 Company overview8.1.8.2 Product benchmarking8.1.8.3 Strategic Initiatives8.1.9 Enlitic, Inc.8.1.9.1 Company overview8.1.9.2 Product benchmarking8.1.9.3 Strategic Initiatives8.1.10 Google LLC8.1.10.1 Company overview8.1.10.2 Financial performance8.1.10.3 Product benchmarking8.1.10.4 Strategic Initiatives8.1.11 H2O.ai.8.1.11.1 Company overview8.1.11.2 Product benchmarking8.1.11.3 Strategic Initiatives8.1.12 HyperVerge, Inc.8.1.12.1 Company overview8.1.12.2 Product benchmarking8.1.12.3 Strategic Initiatives8.1.13 International Business Machines Corporation8.1.13.1 Company overview8.1.13.2 Financial performance8.1.13.3 Product benchmarking8.1.13.4 Strategic Initiatives8.1.14 IBM Watson Health8.1.14.1 Company overview8.1.14.2 Financial performance8.1.14.3 Product benchmarking8.1.14.4 Strategic Initiatives8.1.15 Intel Corporation8.1.15.1 Company overview8.1.15.2 Financial performance8.1.15.3 Product benchmarking8.1.15.4 Strategic Initiatives8.1.16 Iris.ai AS.8.1.16.1 Company overview8.1.16.2 Product benchmarking8.1.16.3 Strategic Initiatives8.1.17 Lifegraph8.1.17.1 Company overview8.1.17.2 Product benchmarking8.1.17.3 Strategic Initiatives8.1.18 Microsoft8.1.18.1 Company overview8.1.18.2 Financial performance8.1.18.3 Product benchmarking8.1.18.4 Strategic Initiatives8.1.19 NVIDIA Corporation8.1.19.1 Company overview8.1.19.2 Financial performance8.1.19.3 Product benchmarking8.1.14.4 Strategic Initiatives8.1.20 Sensely, Inc.8.1.20.1 Company overview8.1.20.2 Product benchmarking8.1.20.3 Strategic Initiatives8.1.21 Zebra Medical Vision, Inc.8.1.21.1 Company overview8.1.21.2 Product benchmarking8.1.21.3 Strategic Initiatives

For more information about this report visit https://www.researchandmarkets.com/r/nr5za

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Insights on the Artificial Intelligence Global Market to 2030 - Featuring Baidu, Clarifai and Google Among Others - PR Newswire

AI Is Not Taking Away Our Jobs Because It Can’t Do Them – Walter Bradley Center for Natural and Artificial Intelligence

In the Top Gun, HAL 9000, and Jobs of the Future podcast (September 15, 2022), WBC director Robert J. Marks discusses whether AI is sucking up all our jobs with talk show host Mark Hahn, who can be heard on KSCJ in Sioux City, Iowa. Dr. Marks, author of Non-Computable You is a professor of computer engineering at Baylor University and a pioneer of AI swarm intelligence. This is the second half of the podcast.

A partial transcript, notes, and Additional Resources follow.

Mark Hahn: Dr. Marks, artificial intelligence is something that many people have fantasized on a science fiction level; many shows have been about that. Of course, in Space Odyssey 2001, HAL took over, and thats what scared people about artificial intelligence. Are we going to be making computers that are smarter than us?

Robert J. Marks: No. Absolutely not. And I dont know if HAL 2000 was smarter than the people. I think it was just programmed incorrectly. It was programmed to put the mission before human life. And I dont know if it was actually took over in any sense.

Note: HAL 9000 was an incredibly knowledgeable AI system that was given one simple order: to make sure that the ship reached its destination at Jupiter. (VillainsWiki) As Dr. Marks notes, AI has no natural ethical system so HAL did not hesitate to plot the deaths of crew members in order to guide the ship to its destination: At one point on the trip from Earth to Jupiter, HAL becomes suspicious that the crew might be sabotaging the mission. HAL then purposely tries to kill all the crew. The most logical explanation for this act is a coding error. HAL was programmed to operate on the basis that the mission took priority over human life. By contrast, science fiction writer Isaac Asimov did not allow his AI to kill. In his work, I, Robot, Asimov proposes three laws for robotics. The first is:

A robot may not injure a human being or, through inaction, allow a human being to come to harm.

If HAL were constrained by this or a similar instruction, there would be no attempts at killing, and 2001: A Space Odyssey would be a much less interesting movie. Could HAL 9000 ever be built? (Mind Matters News)

Mark Hahn: Well, thereve been other books too, along the same line, where man makes a computer, he keeps improving the computer; finally, he wants to have it have a little bit of intelligence on its own, based on, of course, the information that you put into it. And thats what computers are: garbage in, garbage out. If you put good things in there and you build the formats properly for what you want to do, it stays within those parameters. It doesnt go outside, just as you just discussed.

Robert J. Marks: Thats a very good illustration. The idea is that computers and artificial intelligence can take their training data and they can interpolate. They can look inside the box, but they dont have the creative ability to think outside the box.

Mark Hahn: Are future humans doomed to be replaced by artificial intelligence? And of course you said emphatically, No. But what will it replace? Will it replace travel agents? Right now, you certainly have online travel sites that are set up. And you can book in your own travel; you dont need an agent.

Robert J. Marks: You have to ask yourself, can a certain job be described by an algorithm, meaning a step-by-step procedure for doing something? Thats certainly true for travel agents. They go through step-by-step procedures. You hear other things: toll booth operators, for example. Theyre totally gone because they just did a simple algorithm.

Robert J. Marks: So, if your task could be defined by an algorithm, your job is in danger of being replaced by artificial intelligence. But if your position requires sentience, if it requires creativity, if it requires understanding, youre probably in less danger of artificial intelligence taking over.

What is going to happen eventually is, artificial intelligence is going to be a tool. And thats all artificial intelligence is. Its a tool. Its a tool which can be used by different professions to do a better job. But it isnt going to replace them

I would also say that artificial intelligence is going to introduce new jobs. Today we have all of these people that make their living on TikTok or some of these other social media. And we have people that work for Google that do all the censoring of the content. Not a good job. But nevertheless, these are jobs created by artificial intelligence and technology. So, I guess Im a big believer in free enterprise. And it might be painful, but I think that were going to adapt

Note: The Employment Situation Summary compiled by the U.S. Bureau of Labor Statistics for September 2, 2022, reports that Total nonfarm payroll employment increased by 315,000 in August, and the unemployment rate rose to 3.7 percent Notable job gains occurred in professional and business services, health care, and retail trade. 3.7% is not at high unemployment rate, especially if we factor in job changes, etc. If AI is indeed taking all our jobs, it is rather slow about it.

Robert J. Marks: When I was a boy and you made a long distance call, if you went to a payphone, you had to put nickels and quarters in it. And today, I can do FaceTime. Ive done this simultaneously with somebody in Sweden and another person in Colombia. Its just like were in the same room. AI does incredible things.

But as I mentioned in the beginning, theres certain walls that its never going to go through. And I think some of those walls are things like The Terminator and The Matrix. Those things are never going to happen.

Mark Hahn: Well, thats true. Are we ever going to have AI campaign managers in political campaigns? Here we are, coming up to the midterms

Robert J. Marks: I think AI is going to be a tool in this sort of thing. But one of the things that AI doesnt have is creativity. And you can talk about not only campaign managers but, say, a commander in the field.

Now, campaign managers and a commander in the military field are going to face scenarios that theyve never seen before. CEOs of companies do the same thing too. Now, the AI has to be trained in that scenario. If it sees a scenario that it hasnt seen before and its outside the box, if you will, it doesnt know what to do. But people, campaign managers and commanders in the field in the military field are going to have to react and assess situations that theyve never seen before and adapt to them. And no, I dont think artificial intelligence will ever do that. Now, AI might be used as a tool by these people that can give them forecast and suggestions of things to do. But the final decision will always lie with the human.

Heres the first part of the podcast: Marks tells Medved: Top Gun (2022) is way out of date Computer science prof Robert J. Marks argues in Non-Computable You, that in the 21st century, drones offer significant advantages over fighter pilots. But he also warns talk show host Michael Medved, AI is brittle and the ethics factor must be built in. It takes human intelligence to do that.

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AI Is Not Taking Away Our Jobs Because It Can't Do Them - Walter Bradley Center for Natural and Artificial Intelligence

Experts Speak to the Power of Artificial Intelligence for Effective Marketing – Channel Futures

In three to five years, 80% of what marketers do will be dependent on artificial intelligence.

MSP SUMMIT/CHANNEL PARTNERS LEADERSHIP SUMMIT Allison Bergamo knows the power of artificial intelligence (AI) for marketing. Bergamo, principal at Bergamo Marketing Group, uses that kind of AI at her firm because, she said, she wants to be ahead of the curve. Bergamo wouldnt be wrong. As statistics go, in three to five years, 80% of what marketers do will be dependent on this type of technology.

Bergamo Marketing Groups Allison Bergamo

However, its not plug and play, said Bergamo, who added that marketers will have to use clean, unstructured data with some of the technology.

Bergamo was part of a panel of marketing experts who spoke at the MSP Summit/Channel Partners Leadership Summit in Orlando on Thursday. Their advice to the audience spanned from using artificial intelligence technology, to how to master relationships, to learning ways to market on a budget. The latter couldnt be more relevant for MSPs, they said.

Even though many MSPs are small and have finite resources, that doesnt mean they should neglect marketing.

You can find money in your budget to allocate toward this. Its important, said Marcial Velez (pictured right, above), CEO at Xperteks Computer Consultancy. Historically MSPs grow about 10% [annually]. If you want to outperform that rate, youve got to invest in this.

And the investment doesnt have to be expensive, the panelists said. One can be technologically savvy about marketing without spending a lot of money. Velez said digital business cards are a great example because they can share information beyond someones name and company affiliation. Social media and blog posts can also be exchanged with this tool.

You can now start connecting to the content that you want your customers to see right away. You can now show your story, he said.

Charlene Ignacio, CEO (pictured middle, above) at The CMO Guru, HireXPro, also agreed that simplicity goes a long way. She likened it to the difference between buying an expensive Mercedes (a euphemism for a pricey marketing program) and buying a Honda. Everyone thinks they need the Mercedes, she said, even though a Honda can get you where you need to go.

A Honda works perfectly. It will last you 20 years longer, and the maintenance is lower, Ignacio said. When it comes to marketing, I like to do simple things because marketing can become like a black hole (of costs).

However, knowing whether to use cost-effective AI and digital business card tools presumes a certain baseline knowledge by a companys team. If a firm doesnt have that knowledge and needs a marketing program to attain those kind of resources, where do they begin?

Finding a company to outsource ones marketing may be a good first step. And a firm might have luck initially finding marketers who understand its business model. However, the panelists said the likely scenario is that ones first choice of marketers will not work out. Be prepared to fail, they said. But fail fast.

Take Reggie Stevens (pictured left, above), CEO at Iris Solutions, for example. In 2018, Stevens acquired Iris Solutions and set out to find a marketing team.

I didnt know what I was doing, he said.

It turns out neither did the marketers. Yet Stevens didnt spend his time begrudging the fact that he didnt get the professionals he needed to promote his company.

The pandemic made life even more complicated. Stevens knew he needed to keep his community of customers engaged differently because many people were working remotely.

He was steadfast and found another marketing firm.

You know, we had this freak-out moment and we just went back to the basics and started experimenting, he said about his work with the new marketing team. We began differently.

And he started to see results, but it took a year. This is not unusual for marketing initiatives.

Establishing reasonable expectations around how much time it takes to generate a marketing pipeline is critical, he said. It takes a commitment.

However, its even more granular than that. Its a 24/7 process, Velez said.

I think the modern marketer today is someone who looks at marketing more than just an activity, he said. You should automate these systems so that youre continually outreaching and doing things for your existing customers and prospecting for any of your clients.

He added: It takes someone with a really holistic view.

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Experts Speak to the Power of Artificial Intelligence for Effective Marketing - Channel Futures