Welcome to another edition of Talsco Weekly
- IBM i Brief: Eleven new security vulnerabilities on the IBM i. IBM and Salesforce Launch New AI Collaboration.
- Leadership: What is the future of the workplace in this tech driven world? Focus on What Really Matters.
- AI: OpenAI Launches ChatGPT for the Enterprise. Is Nvidia the next Cisco?
- Development: Software Estimates: Fact or Fiction? Python Updates.
IBM i Brief
“IBM on August 18 reported 11 new security vulnerabilities in IBM i’s Java stack, including two critical Java flaws that should be patched immediately. The new batch of vulns continues what has been an active summer for security flaws on the platform.”
If you are using Java, take a quick glance at this IBM i security brief to make sure you are not vulnerable.
IBM Corp. and Salesforce Inc. today announced a partnership focused on helping organizations adopt Salesforce’s artificial intelligence services.
- In March, Salesforce released a suite of generative AI tools called Einstein GPT.
- A tool to assist business tasks such as creating marketing emails and answering customer support inquiries.
- IBM will help joint customers adopt Einstein GPT. The consulting division of IBM will be in charge of the effort.
Career Opportunity: Learn as much as you can about AI related tools (they are just tools) so you can have intelligent and thoughtful conversations around their potential use cases at your company.
“This is a question being asked repeatedly in boardrooms, conferences, and even at universities. Technology is changing the face of the workplace and bringing forth ‘disruptions’ through automation, remote work, and AI, among other things.
“The question becomes:
“In the age of Artificial Intelligence and Big Data, how should companies and businesses nurture, train, and retain human capital?”
Should we hire the way we always have? Or is there a better way?
A Shift in Thinking.
This is tricky because, while there seems to be a focus on new tech (which there should be), it’s more important to think about the intersection of the new and old.
More importantly, how does this intersection of the two play out?
Ultimately, it will be people—those we pick to lead our teams—who develop our software, who lead our companies, that will determine how the game plays out.
When hiring, stop checking boxes.
Does he have this? Has she done that?
Instead, hire with the present and future in mind.
Hire for natural talent.
In the age of AI, there is too much focus on technology.
“AI may augment our mind, but it can never replace the profound wisdom accessible in the state of pure consciousness.” – Bill Fox
Humanity has made significant progress in computing, from machine learning to real-time analytics. These advancements serve as useful tools for amplifying our analytical minds.
However, they are just that—tools.
ChatGPT did not just come out of nowhere, even though it feels like it did.
The history of ChatGPT goes back to June 16th, 2016:
OpenAI published research on generative models, trained by collecting a vast amount of data in a specific domain, such as images, sentences, or sounds, and then teaching the model to generate similar data.
You can find a timeline for ChatGPT here.
While it was only at the end of 2022 that ChatGPT was released to the public, the version for Enterprise is here.
Due to unprecedented demand, OpenAI said that with its launch, it will aim to sign up as many corporate customers as possible.
Since ChatGPT’s launch just nine months ago, we’ve seen teams adopt it in over 80% of Fortune 500 companies. We’ve heard from business leaders that they’d like a simple and safe way of deploying it in their organization.
This is a signal that professionals are using it as a tool to be more productive.
How is ChatGPT being used in the enterprise for software development?
- Code Assistance: ChatGPT suggests code and explanations, aiding debugging and efficient coding.
- Documentation Generation: It creates user-friendly API and software documentation.
- Idea Generation: Developers brainstorm new ideas and features.
- Natural Language Interfaces: Enable software interaction via conversation.
- Automated Testing: Generates test cases for software testing.
- Code Summarization: Condenses complex code snippets for review.
- Code Translation: Translates code between programming languages.
- Prototyping: Generates code structures for quick prototypes.
- Technical Writing: Helps write technical content and tutorials.
- NLP Tasks: Used for text analysis, sentiment analysis, and generation tasks.
We seem to be covering a lot about AI lately.
What does Nvidia do?
Nvidia produces specialized chips (GPUs) and platforms specifically designed for artificial intelligence (AI) and machine learning (ML) tasks.
The future is about GPUs, not CPUs.
GPU’s were originally designed to handle computations related to graphics rendering, but their highly parallel structure makes them more efficient than general-purpose CPUs for algorithms where the processing of large blocks of data is done in parallel. This has led to the adoption of GPUs in a wide variety of applications beyond graphics, such as scientific simulations, financial modeling, and AI tasks including ML.
This is a very interesting read that navigates through significance that Nvidia has on AI or the significance that AI will have on Nvidia. Ultimately, and the effect it will have on virtually all industries and domains.
If GPUs are going to be as big of a market as Nvidia’s investors hope it will be, it will be because applications that are only possible with GPUs generate the demand to make it so.
Are software estimates one of the oldest lies we tell ourselves?
Here are one developer’s thoughts on the topic.
If you are using Python in any shape or form, here are the 3.11.5, 3.10.13, 3.9.18, and 3.8.18 updates.
Why and when should you use Python?
Using Python in an IBM i environment can be beneficial for tasks like data manipulation, automation, and analytics, owing to Python’s rich ecosystem of libraries and its ease of use. Integrating Python can modernize your existing workflows, enabling you to leverage open-source tools and frameworks alongside traditional RPG or COBOL applications.
For example, if you are looking for a web framework when working with Python, Flask might be a good option.
This Deep Dive into Flask Guide provides a roadmap where you’ll crack open the hood to learn about Flask’s internal core functionality to help you build complex web applications.
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