Friday, August 16, 2024

Generative AI Poses Evaluation and Learning Issues as Did Calculators

Educators might say we are at a point with student use of generative artificial intelligence that resembles the teaching and learning of mathematics once calculators were available for use, which is to say a mix of positives and negatives. 


Study Name

Publication Date

Publication Venue

Key Conclusions

The Effects of Calculator Use on Mathematics in Schools and in the Certificate Examinations

2008

Educational Research Centre, Ireland

Calculator use can enhance problem-solving and conceptual understanding, but it's essential to maintain a balance with mental math and paper-pencil skills.

Calculator Use and Mathematical Thinking

1998

The Mathematics Teacher

Calculators can support higher-order thinking skills when integrated effectively into instruction.

The Impact of Calculator Use on Students' Algebraic Thinking

2005

Journal of Research in Mathematics Education

Calculator use can facilitate algebraic reasoning and problem-solving, but it's essential to focus on conceptual understanding.

Calculators in Mathematics Education

1992

NCTM Yearbook

Provides an overview of calculator research and recommendations for effective implementation.


To the extent that traditional exercises, such as writing essays, has been a proxy for testing understanding while arguably improving thinking and writing skills, generative AI poses issues, especially as learning moves away from in-person to online formats. 


In principle, generative AI could enhance creativity, but could also reduce originality; improve writing skills or leave them undeveloped; replace thinking skills or sharpen them; allow personalized learning but also possible plagiarism. 


A  key remaining question is how generative AI affects learning, namely, how humans acquire new skills as they perform tasks. One recent study, for example, involved a thousand students using two generative AI tutors, one that mimics a standard ChatGPT interface (called GPT Base) and one with prompts designed to safeguard learning (called GPT Tutor). 


“Consistent with prior work, our results show that access to GPT-4 significantly improves performance (48 percent improvement for GPT Base and 127 percent for GPT Tutor),” the researchers say. “However, we additionally find that when access is subsequently taken away, students actually perform worse than those who never had access (17 percent reduction for GPT Base).”


In other words, the researchers say, “access to GPT-4 can harm educational outcomes.”


“Our results suggest that students attempt to use GPT-4 as a ‘crutch’ during practice problem sessions, and when successful, perform worse on their own,” the study says. 


One college professor I spoke with noted that her work had switched almost exclusively to online teaching and online testing formats, which means that GenAI use cannot be prevented. 


She noted that GenAI obviously is being used for essays and tests, which does make it harder to assess actual student comprehension of the material, to say nothing of critical thinking, reasoning or writing skills development. 


But one way or the other, schools are going to have to cope with GenAI and its impact on teaching methods, learning and assessment. 


Ultimately, that all will be reflected in labor force skills as well. But cognitive skills will continue to be vital for some industries and job roles, compared to others. 


Industry

Job Function

Higher-Order Cognitive Skills Importance

Technology

Software Engineer, Data Scientist, AI Researcher

High

Healthcare

Physician, Nurse Practitioner, Medical Researcher

High

Finance

Financial Analyst, Investment Banker, Risk Manager

High

Consulting

Management Consultant, Strategy Consultant

High

Education

Teacher, Professor, Curriculum Developer

High

Law

Lawyer, Judge, Legal Analyst

High

Marketing

Marketing Manager, Brand Strategist, Market Research Analyst

Medium-High

Sales

Sales Manager, Account Executive, Sales Engineer

Medium

Manufacturing

Operations Manager, Quality Control Engineer

Medium

Retail

Store Manager, Buyer, Visual Merchandiser

Medium

Hospitality

Hotel Manager, Event Planner

Medium

Customer Service

Customer Service Representative, Call Center Agent

Low-Medium

Administrative Support

Office Assistant, Data Entry Clerk

Low


Thursday, August 15, 2024

How Many Firms Will See Payback on Generative AI, and How Soon?

Though some pioneers claim they already are seeing revenue gains from generative artificial intelligence, we are probably justified in some skepticism about those outcomes.


A Gartner survey of 822 business leaders, conducted between September and November 2023, suggests that various generative AI projects cost between $5 million to $20 million. But that might not be the biggest impact, as costs for inference operations (asking questions, getting answers) could run between $8,000 to $21,000 per user. 


For a 1,000-user firm, that might suggest $8 million to $21 million annually in inference operations. 


source: Gartner 


And there is a bit of a contradiction in the reported results. Gartner notes that GenAI requires a higher tolerance for indirect, future financial investment criteria versus immediate return on investment (ROI). 


That noted, survey respondents have reported 15.8 percent revenue increases, 15.2 percent cost savings and 22.6 percent productivity improvement, on average.


One suspects we should take those quantifiable results with a bit of skepticism, as most of the returns from GenAI are indirect and hard to measure. 

There’s a reason increasing use of generative and other forms of artificial intelligence is linked to data center capacity: model training is getting more compute intensive. So large language model training costs are growing. 


And model creation and training might not be the biggest cost. 


 

source: Epoch AI


Some of us would not be at all surprised if disappointment with GenAI outcomes becomes more pronounced as projects seem not to provide the anticipated financial outcomes, in the near term. 


To the extent AI is the next general-purpose technology, as was the internet, we could ask the same questions about near term return from internet investments. 


How many firms will see near-term and quantifiable revenue upside from their capital investments and operating expenses directly related to GenAI? 


Outside of graphics processing unit suppliers; cloud "AI as a service" providers and big system integrators such as Accenture--who should be able to point to quantifiable revenue gains--not many end user firms will be so lucky.


We are likely years away from a substantial number of firms being able to say they can quantify revenue gains from using GenAI.




Tuesday, August 13, 2024

"You are the Product" Works Because Users Get Value

It is commonplace these days for observers to note that if a user is not paying for a product, then the user is the product. Sometimes that is viewed as a bad thing, but there is a bargain being struck here: users get value in exchange for being subjected to advertising.


And that is a time-tested value proposition. Users and customers get free or reduced-cost products they value for less money than would otherwise be the case. 



Product

Form of Subsidy

Value for Users

Free Online Games

In-app purchases, advertisements

Free gameplay, access to new levels/characters

Free Mobile Apps

In-app purchases, advertisements

Free core functionality, additional features for purchase

Free Video Streaming Services

Subscription model, advertisements

Free access to content, ad-free viewing option

News Websites

Advertisements, paywalls

Free access to news content, in-depth articles for subscribers

Social Media Platforms

Advertisements, premium subscriptions

Free connection with others, enhanced features for paid users

Free Email Services

Advertisements, paid storage upgrades

Basic email functionality, additional storage and features for a fee

Open-Source Software

Donations, corporate sponsorships

Free access to software, potential for customization and improvement


In principle, other forms of subsidy, discounts or premium value also are common. 


Product

Value for Users

Wholesale Clubs (Costco, Sam's Club)

Bulk discounts on groceries and household goods

Streaming Services (Netflix Premium, Spotify Premium)

Ad-free viewing/listening, access to exclusive content

Gyms and Fitness Centers (Monthly Memberships)

Access to workout facilities, classes, and potentially personal training

Subscription Boxes (Beauty, Food, etc.)

Curated selection of products delivered regularly, often at a discount

Cloud Storage Services (Dropbox Plus, iCloud+)

Increased storage capacity for documents, photos, and other files

Software Subscriptions (Adobe Creative Suite, Microsoft 365)

Access to the latest software updates and features, often with cloud storage included


The point is that as much as some decry the use of advertising, sponsorships and memberships, these are simply ways of creating value for buyers, offering lower prices and discounts, free access or perceived higher value. 


Monday, August 12, 2024

AI to Boost ASIC and FGPA Sales

As artificial intelligence is driving demand for data center capacity, connectivity and graphics processor units, so AI should increase demand for Application-Specific Integrated Circuits (ASICs) and Field-Programmable Gate Arrays (FPGAs). 


Perhaps the only question is what the rate of growth might be. 


According to MarketsandMarkets, the global AI chip market is expected to grow from $7.6 billion in 2020 to $57.8 billion by 2026, at a compound annual growth rate (CAGR) of 40 percent. 


Study Title

Publication Date

Publisher

ASIC Market Growth (CAGR)

Artificial Intelligence Chip Market - Trends, Forecast and Competitive Analysis

May 2024

Mordor Intelligence

32.50%

The Future of AI Processors: A Comparative Analysis of ASICs, FPGAs, and Neuromorphic Computing

March 2024

McKinsey & Company Report

35.8% (High Performance)

AI Hardware Market: 2024-2029

July 2024

Grand View Research

31.20%

The Rise of Domain-Specific Architectures for AI Workloads

June 2024

Gartner Research Report

38.1% (Forecast to 2027)

How AI is Transforming the Semiconductor Industry

February 2024

Deloitte Insights Report

34.70%

Data Center Capacity to Double Over the Next Four Years

Amazon, Microsoft and Google now represent 60 percent of all hyperscale data center capacity, while doubling their capacity over the last four years, says Synergy Research. The firm expects total hyperscale data center capacity will double again in the next four years.


Synergy Research sees non-hyperscale colocation data centers accounting for 22 percent of worldwide capacity, with on-premise data centers rounding out 37 percent of the total. 


source: Synergy Research


In turn, that capacity drives demand for connectivity as well, as a huge portion of global long-haul capacity is used to connect data centers. Estimates peg the percentage of “data center to data center” capacity between 30 percent to 50 percent of total. Add in connections to internet points of presence and as much as 75 percent of total global backbone networking capacity connects data centers with other data centers and internet points of presence. 


Category

Global Capacity

Data Center Interconnections

30-50%

Internet Points of Presence (PoPs)

30-40%

Enterprise Networks

10-15%

Other

5-10%


The advent of artificial intelligence is likely to drive capacity trends. 


The AI "data center to data center" interconnection services market is expected to grow from $4.2 billion in 2023 to $9.1 billion by 2027, a CAGR of 16.8 percent, according to analysts at Gartner.


Gartner also forecasts the overall "data center to data center" capacity market is forecast to grow from $48 billion in 2023 to $72 billion by 2027, a CAGR of 10.6 percent.


According to IDC, the AI-driven "data center to data center" interconnection services will account for 22 percent of the total "data center to data center" capacity market by 2025, up from 15 percent in 2023.


The global "data center to data center" capacity market is projected to reach $64 billion by 2025, growing at a CAGR of 12.7 percent from 2023, IDC also believes.


Forrester researchers believe the market for AI-enabled "data center to data center" interconnection services will grow at a CAGR of 19 percent from 2023 to 2027, reaching $8.5 billion by 2027.


Forrester also estimates the overall "data center to data center" capacity market will grow at a CAGR of 11 percent from 2023 to 2027, reaching $68 billion by 2027.


Markets and Markets predicts the AI "data center to data center" interconnection services market will grow from $4.6 billion in 2023 to $10.2 billion by 2027, at a CAGR of 17.3 percent .The global "data center to data center" capacity market is forecast to grow from $51 billion in 2023 to $78 billion by 2027, at a CAGR of 11.2 percent, the firm says. 


The point is that if data center capacity keeps doubling every four years, then  “data center to data center” connections are going to grow as well. The issue is “how much” growth will be needed and how long the trend might last.

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