Welcome to another edition of Talsco Weekly
- IBM i Brief: Subscription pricing trend continues. More predictions for the IBM i in 2024.
- AI: Watsonx and other AI platforms. The future of ERP in the World of AI.
- Career: Trends in the World of AI. The Home Office vs the Office.
- Development: SQL Error Logging Facility. Build and IBM i app tutorial.
IBM i Brief
Subscription Pricing for IBM Cloud Storage and BRMS
IBM introduces subscription pricing for IBM Cloud Storage and BRMS IBM is transitioning its software stack, including IBM Cloud Storage and Backup, Recovery, and Media Services (BRMS), from perpetual licensing to subscription pricing.
See the pricing charts for both cloud storage and BRMS here.
The IBM i predictions for 2024 continue
It is anyone’s guess if any or all of these come true throughout 2024. There are some interesting takes on the following: Training, AI, retirements, cloud workloads for IBM i, and the expansion of one segment of the IBM i community (this may or may not surprise you).
Key Takeaways:
- The market for AI will start to play out in 2024, with one of the major players in the digital transformation space (Profound Logic) launching their new AI product.
- With many IBM i professionals stepping into or considering retirement, there is a shift taking place with the newer generation of talent coming into the market. This is pushing the adoption of new tools that help with automation.
“IBM (IBM) reported revenue rose 4% last quarter, driven in part by demand for its AI products and services as well as its hybrid cloud. The computing giant also said free cash flow will improve this year.”
I would be curious what percentage of IBM sales are attributed to Power Systems in 2023. Power Systems revenues (including Power-based storage) in 2022 were about $1.42 billion.
AI
Watsonx: Unveiling the future of AI integration
While there is no shortage of AI platforms out there, “Watsonx is the AI and data platform that’s built for business.”
Watsonx is made up of three components: foundation models, generative AI and machine learning.
Foundation Models: Foundation models are large-scale, versatile AI models trained on extensive datasets, enabling them to perform a wide array of tasks, even those beyond their initial training scope. They are used as a base for developing more specialized AI applications, offering benefits like adaptability and efficiency in handling complex tasks such as language translation and content generation. Foundation models are the underlying technology that powers generative AI.
Generative AI: AI models are designed to generate new content or data that resembles the training data but is original. This includes generating text, images, music, and other media. The purpose: The primary goal is to create new, coherent, and contextually relevant outputs based on learned patterns from the input data.
Machine Learning: Machine Learning (ML) is a fundamental component of AI platforms, serving as the core mechanism through which these platforms learn from data, make predictions, and improve their performance over time. ML is the driving force, of an AI platform that enables it to learn, adapt, and provide intelligent solutions across various domains and applications.
Why is this important? AI is changing the approach organizations are taking to Modernization projects. A shift is taking place. While many ERPs are or have incorporated AI into their solutions, some legacy ERP shops are taking a different approach.
Many, IT leaders are realizing their money is better spent upgrading their existing ERP and then investing in AI and other digital transformation solutions.
What do you think?
Other notable AI platforms
Watsonx is by no means the only game in town. Here are some others, with new ones coming to market every day.
Google AI Platform (now part of Vertex AI): Offers a comprehensive suite for machine learning, from data preparation to model training and deployment. It’s integrated with other Google services, providing a seamless experience for developers.
Microsoft Azure AI: A set of AI services and cognitive APIs that enable developers to build intelligent applications. It includes services for vision, speech, language, decision, and search functionalities
Amazon Web Services (AWS) AI: Provides a broad array of AI and machine learning services, including text-to-speech, translation, image and video analysis, and personalized recommendations.
Salesforce Einstein: Embedded directly into the Salesforce platform, Einstein uses AI to enhance customer relationship management (CRM) by predicting customer behavior, automating tasks, and providing insights.
OpenAI: Known for developing advanced models like GPT-3 and DALL-E, OpenAI offers powerful language and image generation capabilities that can be integrated into various applications.
TensorFlow by Google: An open-source machine learning framework that is widely used for research and production. TensorFlow supports a range of tasks and is particularly popular in deep learning applications.
Career
Career Trends and Predictions for the future
While it might be true that AI will eliminate some of the work we do, it seems clear that like with all new technologies, it simply creates more opportunities elsewhere. And often times, it makes certain skill sets even more important than they were before.
As this article suggests:
The demand for “human” skills will only continue to rise because of emerging technology and automation. Holistic skills — communication, collaboration, analytical thinking, and innovation — will be critical for new technical roles created by AI. Curiosity will also rise as the No. 1 skill needed. According to ServiceNow’s research with Pearson, 71% of U.S.-based admin assistants are strong candidates for help desk agent and similar roles. Bringing together information to solve challenges and asking the right questions will be critical as generative AI and prompting will continue to be more prevalent in the new year.
Study Reveals Workplace Mandates Fail to Boost Company Profits
While the majority of openings that we are seeing are either hybrid remote or fully remote, there are still organizations that are pushing people back to the office.
A recent article reports that:
“IBM Consulting this week told its US-based executives and people managers that, effective immediately, they must work from a corporate office at least three days per week, or face the consequences.”
On the other hand,
“New research shows that return-to-office mandates don’t play any role in a company’s financial performance but do have negative side effects for its workforce.”
What do you think?
Development
SELF, or SQL Error Logging Facility, was introduced in IBM i 7.5 TR1 and 7.4 TR7, as a way to capture SQL errors and insert them into a table that can be used to diagnose and remedy those errors. There was a drawback with the tool, which has been recently updated with the latest Technology Refreshes, IBM i 7.5 TR3 and 7.4 TR9. Learn more here.
Video tutorial: Building an IBM i app 🎥
Liam Allan guides you through the process of creating a new program, display file, and database integration that can then be further extended to be used by other programs.
Tools used: VSCode, Code for IBM i, Source Orbit, and IBM i CI.
Here is a shorter version.
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