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Question: 1
You are investigating a slow-performing expression rule and want to analyze this rules historical performance.
Which performance log should you look at to see the mean evaluation time of this rule every hour?
A. expressions_details.csv
B. expressions_metrics.csv
C. expressions_summary.csv
D. expressions_trace.csv
Answer: A
Question: 2
You are creating a table to store book information for a library. The boot has a reference number (ISBN_ID), as well
as a unique identifier (BOOK_ID).
For the CDT to be created, which data type should you choose for the BOOK_ID? (Choose the best answer.)
A. Number (Integer)
B. Number (Decimal)
C. Date
D. Boolean
Answer: A
Question: 3
Which XSD element is NOT supported within an Appian CDT? (Choose the best answer.)
A.
B.
C.
D.
Answer: B
Question: 4
Which review format is the most efficient way to coach team members and Boost code quality? (Choose the best
answer.)
A. Peer Dev Review
B. Automated Code Scanning
C. Retrospectives
D. User Acceptance Testing
Answer: A
Question: 5
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You are code-checking your colleague's process model before marking it as Ready for Deployment.
Which three best practices should be applied? (Choose three.)
A. All nodes should have exception flows
B. All XOR/OR gateways should have a single incoming ow.
C. All outgoing flows from a gateway should be labeled
D. Node inputs should not make the same query call more than once.
E. Activity chaining should be added to the majority of flows.
Answer: A,B,C,D
Question: 6
Which user role should be used to allow external systems to invoke Appian web APIs?
A. Service Account
B. System Administrator
C. Application User
D. Designer
Answer: A
Question: 7
What are three things you can do to Boost the memory usage of a process model? (Choose three.)
A. Configure process variables to be parameters.
B. Reduce the number of process variables.
C. Avoid storing large blocks of text in process variables.
D. Split large nodes into many smaller nodes.
E. Pass data directly to activity nodes and smart services.
Answer: A,B,C,E
Question: 8
You need to display the profile picture of each employee inside an employee grid, alongside their names and phone
numbers.
According to Appian best practices, what is the preferred style and size for the images?
A. style: AVATAR
size: LARGE
B. style: STANDARD
size: ICON
C. style: STANDARD
size: LARGE
D. style: AVATAR
size: SMALL
Answer: D
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Question: 9
Which two practices are strongly discouraged for activity chaining? (Choose two.)
A. Less than or equal to 5 seconds between attended activities.
B. More than 50 node instances
C. More than 5 seconds between attended activities
D. Less than or equal to 50 node instances
Answer: A,B,C
Question: 10
Your organization requires a process to be initiated via an Appian web API.
Which HTTP request methods should the API use?
A. HEAD
B. GET
C. POST
D. CONNECT
Answer: C
Question: 11
You are referencing and using arrays of a CDT (Custom Data Type).
Which two statements are true? (Choose two.)
A. Other Appian functions can be used within the square brackets [] when using dot notation to return specific data
from the array.
B. There is no difference between using dot notation and the index() function.
C. An array of integers can be passed as the second parameter to the index() function to return the data at those
position in the array.
D. The function wherecontains can act on operands of different types.
Answer: A,B,C
Question: 12
Your table contains several indexes.
Which two statements regarding indexes are correct? (Choose two.)
A. Indexes increase the performance of Read operations.
B. Indexes increase the performance of Write operations.
C. Indexes decrease the performance of Write operations.
D. Indexes decrease he performance of Read operations.
Answer: A,C
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Question: 13
Your organization is in the process of redesigning its user interfaces in order to use space efficiently.
Which layout component is most appropriate for displaying the interface where the meaningful order of components is
vertical?
A. a!columnsLayout()
B. a!columnOverlay()
C. a!cardLayout()
D. a!sideBySideLayout()
Answer: A
Question: 14
You have been asked to produce a Tempo report, with the following requirements:
The report should display in Appian.
The data is held in a business database, but performance in Appian is a key requirement.
Which three actions can you take to minimize the performance impact of your report? (Choose three.)
A. Display the report as a task report on the Tasks tab.
B. Limit the number of series values and categories in the report.
C. Use local variables in your report interface to avoid redundant database queries.
D. Use the query process analytics function to retrieve the data.
E. Perform aggregation in the database using a view prior to studying the data into Appian.
Answer: A,B,C,E
Question: 15
Your organization is considering automating the running of expression rule test cases to provide unit tests for your
Appian applications.
Which three methods could be used to launch a test run when required? (Choose three.)
A. Via the DevOps section of the Administration Console.
B. A process model invoked via an AP
C. A process model exposed to users as an action.
D. A web hook from a content versioning system (CVS).
E. A SAIL interface embedded in a report.
Answer: A,D
Question: 16
What is the lowest permission required on the data store in order to query, write, and delete data?
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A. Manager
B. Administrator
C. Viewer
D. Editor
Answer: C
Question: 17
You are required to test a Related Action that updates record data. You need to make sure that the correct users can
access the form and that the data is updating successfully.
Which is the most appropriate testing method to achieve this using Appian?
A. Unit Testing
B. User Interface (UI) Testing
C. Load Testing
D. Performance Testing
Answer: A
Question: 18
You are using pie charts.
What is correct representation of Appian best practices? (Choose the best answer.)
A. Use as many slices as possible.
B. Pie charts should only be used to represent data that can be placed into identical categories.
C. Use pie charts to show proportional data.
D. Try to use multiple pie charts when comparing multiple sets of data.
Answer: B
Question: 19
There is a need to relate two entities in the data structure: Employee and Skill.
Employees can have multiple skills, and a single skill can relate to multiple employees.
What kind of relationship would these entities have, and what is the minimum number of tables required to implement
the design, according to Appian best practices? (Choose the best answer.)
A. One-to-many; 2 tables
B. Many-to-many; 2 tables
C. Many-to-one; 2 tables
D. Many-to-many; 3 tables
Answer: D
Question: 20
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HOTSPOT
You need to create and design an ERD that represents the clients bookstore inventory.
Match the entity descriptions to the most appropriate relationship. Each relationship type will be used once.
wrong
Answer: D
Question: 21
You are analyzing a poorly-performing process model.
You find that the process model in question has a lot of nodes and is mainly used to do background updates.
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Which two things can be done to increase its performance? (Choose two.)
A. Define the correct alerts for the process model.
B. Remove all activity chaining.
C. Use swim lanes in the process model.
D. Refactor some nodes into subprocesses when possible.
Answer: A,B,D
Question: 22
You need to build a process model that transforms a large data set.
Which two things should you ensure to include in your process model? (Choose two.)
A. A subprocess is called using Multiple Node Instances (MNI) to perform the transformation on each item in the
data set.
B. An XOR gateway is added before the transformation node, to check for empty/null values.
C. A loop is created within the process model that increments on each iteration, updating that particular row in the data
set.
D. The transformation is applied with an expression rule that takes the data set as an input, and loops through the
dataset using a looping function, such as foreach.
Answer: A,B,D
Question: 23
You are creating an ERD that models the data for a college and includes a Many-to-Many relationship, Student-to-
Class, where a student can be enrolled in multiple classes, and a class can enroll multiple students.
How can you handle this relationship so that it can be supported in Appian and remain in at least First Normal Form?
(Choose the best answer.)
A. A joining table can be used to hold instances of Student/Class relationships.
B. The Student table should have a Class field to hold an array of Class IDs.
C. The Class table should have a Student field to hold an array of Student IDs.
D. It cannot be done, because Appian CDTs cannot handle Many-to Many relationships.
Answer: A
Question: 24
An organization has decided to integrate with a third-party to scan incoming documents and capture the details in a
table called [appian].[document]. Each document will form a new case in Appian to be displayed on a Record List.
The record needs to show data from both [appian].[document] and [appian].[caseData], which holds additional case
information.
What is the most efficient way to achieve this?
A. Create a trigger on the [appian].[document] table to copy all the data across to the [appian].[caseData] table and
point the record at [appian].[caseData].
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B. Create a SSIS package to run at a regular interval.
C. Create a view between both the [appian].[document] and [appian].[caseData] tables to feed the record.
D. Create a stored procedure to query the data from both the [appian].[document] and [appian].[caseData] tables.
Answer: C
Question: 25
You are troubleshooting slow response times on a SAIL interface.
What are two potential causes of the performance issues? (Choose two.)
A. Multiple rule inputs
B. Multiple a!save operations
C. Configuration of refresh variables
D. Stacked button layout
Answer: A,B,C
$13$10

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Thu, 04 Jan 2024 20:00:00 -0600 en-US text/html https://www.techrepublic.com/article/the-ultimate-artificial-intelligence-machine-learning-e-degree-bundle/
AI without training? It can be done, argues Appian CEO Matt Calkins

The world is currently full of `hot’ stories about where AI is going to take us, and do to us, and the state we will be in by the time it has finished with us. It is true that it may gain some semblance of sentience at some time in the future, but it is far from that at the moment. And the argument now is very strong that the `A’ is AI should stand for 'Augmented’ not 'Artificial’. When looked at that way the obvious question for potential users then becomes `what do you want augmented – what help do you need to augment it, where in any process do you need it, and how do you make it happen?’

This subject was addressed at a exact London conference hosted by low-code/business process management vendor, Appian. CEO Matt Calkins side-stepped the hype and used his keynote address to set about outlining where AI is going to help in that all-important area of `making businesses run better’ over the next couple of years.  It was, therefore, low on scary content, but did address the underlying reality that business managers will need to be ready for the significant changes already barrelling down on them if they are not to be caught unawares and unready: 

We need to move from hype to reality. We've talked a lot about how AI can get us to an amazing place. Now we need to figure out how we actually go there: where are we actually trying to go with this technology? AI can take us to a human centric future. AI is going to be a partner instead of a substitute for people.

Calkins also sees the coming changes being more democratically available to businesses of all types and sizes rather than exclusively for large enterprises, a view he suggested is different from current conventional wisdom. And it's different from the view of the investment community as well, which has so far bet heavily on the big technology names because, as he put it, investors believe that they're going to use AI as a tool to gain advantage over all the rest of us: 

I think investors think Big Tech is going to find a way to use AI to get our data, take our money, put us in a position where we have to rent the best technology in our entire enterprise. But we have to move our conversation away from wild predictions and toward demonstrations of effectiveness of AI in the workplace.

Don’t waste your data

What Calkins sees is a need for users to understand that AI in the workplace is not a standalone technology, rather, it is symbiotic with - even dependent on - two other areas, data and process, without which it will not have any tangible effect. He sees it as a triangle of these three primary, interdependent and synergistic areas:

AI without data would be like a card trick with no cards. It is just re-shuffling cards, just re-shuffling data; taking what it's learned, putting it into a new configuration, and putting it back out to you.

Current models have it that AI is not only dependent on data, but also dependent on two data sources: the `past’ in the form of a training data set, and the data that comprises the ‘present’. AI then relates the two of those together.  Therefore, the value of the data presented is key to the value that comes out of any AI process. In Calkins’ view most data today is waste. For example, most data that's known to organisations is not utilized properly because it's not brought to bear at the moment of decision. The moment a customer calls a call center, that's when a business needs to know about that customer in order to react properly. If that does not happen, (within 10 seconds, in his opinion) then the data is effectively wasted.

He sees AI solving much of this, allowing data to be accessed in real time…in theory. In practice, this will depend on the effectiveness of the interface between AI and the rest of the business. This is an area Appian is focussing on, but Calkins has doubts about how many users are aware of it, or the value of it. Added to that is then the business need to understand how best to get to that value:

I'd say your data is maybe double as valuable as it was a couple of years ago. And most people don't realise that they haven't really talked about it. AI isn't 100% reliable. Instead, we are entering a long term period in which AI will write, but humans will edit, AI will propose, humans will decide. It's a team effort that's going to last a long time.

One of the keys here, so far as Calkins is concerned, is Appian’s development of its Data Fabric, which has clocked up 4 billion queries despite still being rolled out to all of the users of the software. The amount of effort put into developing and implementing Data Fabric has led Calkins to suggest that Appian has got close to becoming a Data Fabric company, specialising in the development and application of the technology above and beyond everything else. 

Doing AI without training

Its importance to the application of AI by the company can now be seen as some explanation for the effort that was made. That all hinges round Calkins’ enigmatic statement to the conference delegates:

We're not going to try to take your data; we want to facilitate the enterprise that you've already got.

This has to do with the way that current AI implementations tend to work in practice, where a user’s data can be at risk as a core part of the process, while it is being used. The Appian Data Fabric is at the heart of this because it connects the entire enterprise via what is, in effect, a virtual database layered across all the data sources that exist in that enterprise. This allows users you to run rapidly-built queries and get answers based on the latest live information from any data source connected to the Data Fabric. with full row-level security. 

Calkins was eager to stress that the provision of row level security plays a vital role in the implementation of AI for practical business applications, not least because the fear of many businesses that using AI services puts their data at risk is very real for them. After all, it is the way that most AI services now operate. Most of the services are only available via the mainstream public cloud service providers, so in order to train a Large Language Model service in its particular business and requirements, a user company first has to upload its data to the service.  

We believe that it is a non-starter to load your data, especially enterprise data, onto a public AI platform, just a non-starter.

His point here is that in order to train an AI system sitting on a public cloud service, a business has to feed it with its own real data, and that makes it difficult to definitively claim that it owns that data any more. As an operating model, it does mean they can then work well - questions can be sent, the context derived from the training data and an answer delivered - but a company may have difficulty claiming in  now 'owns’ its data, and it has to keep feeding in new data to the training process. 

One way round that is for a company to install an open source AI inside its firewall, training and using it effectively 'on-premise’. The downside here is that it then requires both a high level of expertise on the part of staff, and a high level of ongoing, dedicated investment to keep the service level up to scratch. So Appian is in the throes of developing a new model for utilising AI that prioritizes data security and, as an added advantage, is expected to be faster, more accurate, and less complex in operation.

The third way to do it is to put a generic, plain vanilla AI in a private cloud space, and then inform it in real time. This is where having a Data Fabric available becomes important. Before a question is actually posed to the AI service a query is run against the entire enterprise data set, a task that requires a Data Fabric. This surfaces all the company data relevant to the query and this is sent, together with the question, to the vanilla AI service in a private cloud. Combining the question with all relevant current data extracted from the live business applications gives the AI the not only the information but also the context underpinning the question.

This will make it far more secure, for the data can be deleted as soon as the result has been accepted. It will also be more cost-effective as users will not have to pay to store large amounts of training data, ongoing data upload fees and running costs of a large cloud services site. Finally, its answers are auditable. The source data can be filtered to remove information that is not relevant for the question being asked, which can also help manage the introduction of accidental biases.

My take

If AI achieves anything over the next few years it will be an almost brutal demonstration of the famous Gartner Hype Cycle in action. At the moment, the expectations for AI are humungous – and continuing to grow – with possible results for humanity ranging from a future life of enduring, blissful indolence to total annihilation. So reaching the 'Peak of Inflated Expectations' still seems a long way off. The subsequent fall into the 'Trough of Disillusionment', when it comes, will no doubt be equally rapid – with the likelihood of many corporate fingers being badly burned.

But as and when AI moves on to the Plateau of Productivity, an operational model such set out by Calkins is likely to be playing a significant part in achieving that goal. It targets a role for AI that just about every business will need at their core, whatever their size, and offers a way of achieving it, if Calkins proves right, that offers speed, flexibility, accuracy and, above all, greater security.    

Thu, 21 Dec 2023 00:18:00 -0600 BRAINSUM en text/html https://diginomica.com/ai-without-training-it-can-be-done-argues-appian-ceo-matt-calkins
Best Scrum developer certifications

Best Scrum developer certifications

As big tech companies including Twitter and Facebook lay off thousands of programmers, the job market becomes increasingly competitive.

As such, developers who seek gainful employment and top-tier compensation must find ways to set themselves apart from the crowd. One of the ways to do that is to complement your education and work experience with certifications that are highly in demand and respected in the industry you’re in.

For Scrum developers who wish to find work on cross-functional and self-managed Agile teams, here are the top 5 Scrum developer certifications:

  1. Professional Scrum Developer Certification
  2. Certified Cloud Developer
  3. Certified Java Programmer
  4. Certified DevOps Engineer
  5. Certified Kubernetes Professional
Scrum Commitment and Values

A certified Scrum developer understands the importance of the five, core Scrum values.

Professional Scrum Developer Certification

Employers want developers that are immediately productive. They don’t want to waste time explaining software development processes and procedures to new hires.

When a Professional Scrum Developer Certification appears on a programmer’s resume, an employer knows that the application fully understands the following:

  • the intricacies of iterative and incremental development;
  • the importance of the product backlog;
  • what to do during the daily Scrum; and
  • how to participate on a cross-functional team.

Relatively few programmers are certified as Scrum developers. A developer this certification on their really stands out from the crowd.

Developer certifications in Scrum can be obtained by several organizations, but the premier designation comes from scrum.org.

Certified cloud developer

Modern software development happens in the cloud.

A productive software developer on a Scrum teams must know how to provision cloud-based resources, troubleshoot code in the cloud and overcome cloud-based security and firewall issues.

Employers know that the ability to develop and manage cloud-based applications is essential to modern-day businesses. A cloud developer certification on an applicant’s resume tells the hiring manager that you understand and can take full advantage of the benefits of cloud computing for a software development team.

All of the major cloud vendors offer a cloud developer certification. Cloud developer certifications from Google, Amazon and Oracle are all held in high regard.

Certified Java Programmer

Organizations expect a software developer on a Scrum team to know how to write code. Therefore, every Scrum developer should have a some type of a programming language certification on their resume.

For example, I like to see a Certified Java Programmer designation from Oracle on a resume, even if a company’s main language is Python or JavaScript.

A Java programmer certification proves a developer knows the following:

  • programming fundamentals
  • object-oriented concepts
  • functional programming
  • common design patterns

Industry-recognized certifications in other languages, such C# from Microsoft, also demonstrate to potential employers that you have a strong grasp of programming fundamentals.

Certified DevOps Engineer

Agile’s highest priority is the continuous delivery of software.

An Agile Scrum developer must understand the toolchain that enables continuous software delivery. DevOps certifications proves one’s knowledge of that toolchain.

The two most highly coveted DevOps certifications come from Amazon and Google. Both are considered ‘Professional’ designations, which means they go further in depth than introductory or associate certs.

Both the AWS and GCP certifications cover the same breadth of topics, including how to:

  • implement and manage continuous software delivery systems;
  • integrate with version control tools including Git and GitHub;
  • create resources with infrastructure-as-code tools such as Terraform;
  • deploy monitoring, logging and metrics gathering systems; and
  • manage Docker- and Kubernetes-based deployments at scale.

A Scrum developer certified by Amazon or Google as a DevOps Engineer brings a qualification to the table that few other job applicants possess.

Agile and DevOps Differences

The DevOps infinity loop shows an iterative dev process often embraced by Agile teams.

Certified Kubernetes Application Developer (CKAD)

A Kubernetes certification is rare, but it’s definitely a plus.

A developer with strong knowledge of cloud-native computing, 12 factor app development and the limitations of Docker and Kubernetes will help streamline an organization’s microservices development and play a key role in its digital transformation efforts.

The CKAD designation is provided through the Cloud Native Computing Foundation, a highly respected open source organization in the cloud native computing space. Scrum developers with this certification have proof of competency in the following areas:

Scrum development teams that build cloud-native applications that are managed at runtime by Kubernetes will be well-served to have a Certified Kubernetes Application Developer.

Scrum developer certification benefits

In a competitive job market, it is important to stay ahead of your competition. With these five Scrum developer certifications on your resume, you will find your Agile development skills in great demand.

Mon, 09 Jan 2023 10:01:00 -0600 en text/html https://www.theserverside.com/blog/Coffee-Talk-Java-News-Stories-and-Opinions/best-scrum-developer-certifications-agile-developer-programmer
The Role Of Low-Code In AI Software Development

AI is big. The deployment of Artificial Intelligence (AI) continues to dominate the software application development landscape with commentators, industry analysts, AI evangelists and chief AI officer (CAIO) positions now being created as adjuncts to the traditional C-suite tech leadership roles.

The conversation in this space appears to circulate between the backend infrastructure we will require to handle the compute power needed for AI, through the middle tier where the industry is starting to worry more pressingly around guardrails and AI’s exposure to Personally Identifiable Information (PII)... and then onward to the upper tier of the applications themselves with the use of co-pilot tools for humans and the looming spectre of AI bots having (and indeed populating) their own social media accounts.

As this move to mainstreaming predictive, reactive and of course generative AI has continued, many of the new services we’re seeing are making use of Natural Language Processing (NLP) techniques at their heart to drive the use of Large Language Models (LLMs). Notable examples include OpenAI’s GPT, PaLM from Google AI being used to power Bard, Anthropic’s Claude AI, Meta’s LLaMA, BLOOM and Ernie Titan. As a core chunk of algorithmic logic, most organizations don’t have the resources, time or skills needed to create their own LLM, so this reality again fuels industry chatter around which LLM to use and how closely we need to look at its DNA.

Given the complexity that we face here (in the pursuit of simplicity), how should IT teams think about their use of these core components of AI and what automations are available to make the process easier?

The right foundation foundations

“The first step when considering different LLMs is to identify an organization’s business problem or an opportunity for improvement. We can then move to understand the tasks, processes and people involved to establish clearly defined use cases. It’s important to realize that different LLMs have different architectures, training data, strengths and suitable use cases,” said Ysanne Baxter, solutions consultant at low-code software platform and process automation company Appian. “Commercially available LLMs are often used as a base model in other projects, which provides a platform to introduce further bespoke or specialized tasks. Designed for flexibility and scalability, these language models generally yield better results when the foundation dataset is vast, diverse, and complex.”

Baxter explains that the differences are down to LLM architecture, potentially resulting in different outputs. For a start, a model needs to have a vast body of textual data to draw from - let’s say, a set of customer reviews about a product or service - and if an organization’s objective is to determine the reviews’ main points or themes, it could then use findings to generate a set of responses and new features to Boost the offering. Baxter says that multiple models could help tackle this kind of task and there are tools to make it possible to train multiple models at once. Software developers can then assess the real metrics after this process is complete, enabling them to compare these outputs to help guide their assessment of which is likely to be the best fit.

Ultimately, the question is: which is the most appropriate LLM for the task? If an organization has framed its problem (or opportunity) well and understands the data it has to work with and the desired outcomes, then it has a good foundation to start with when assessing models to find the best fit for the task at hand.

Low-code accelerators

“Tackling ML/AI is no small feat and knowing where to start can be overwhelming. Low-code development tools can make this undertaking significantly more accessible with a common language,” asserted Baxter. “Developers could use low-code tools to draw on expert teams with a deep understanding of these technologies. We don’t need to individually define a new model from scratch to perform every new task, but instead, we could use their deep research and development of ML/AI tools to help us achieve the same objectives. Low-code approaches essentially become a multi-disciplinary collaboration in this way: taking that expertise and adding our own, applying it in a way that’s deeply relevant to our organization in a fraction of the time.”

The Appian team say that there are plenty of use cases where existing low-code AI tools are appropriate and sufficient. For example, many email providers already use NLP to help classify and separate spam from an inbox. Developers could use low-code tools for appropriate AI use cases for productivity gains, as it would be very time-intensive to keep engineering similar products or features anew.

“Ultimately, low-code tools allow developers to build on the best in our industry. Like in academia, quality research always builds on what came before; it can break new ground, but there’s always the context of the existing body of work. When one applies low-code approaches to create new AI solutions leveraging an existing LLM, the result is hyperproductivity, output and impact in accelerated time,” advised Baxter. “Protecting or omitting personal and mission-critical data requires a thoughtful approach at every step of development. With an ‘out of the box’ LLM, there is little to determine what qualifies as sensitive data. You could put your UK national insurance or US social security number into ChatGPT and as far as I know, there is nothing, in the model alone, to stop it from being ingested and shared in full.”

Open or closed source?

While we’re busy working out how to assemble the componentry inside our AI models and where to make LLM connections, there’s also a lot of plenty of debate as to whether we should be adopting open source or closed source models, datasets and perhaps today (what with the amount of licensing change we have seen in exact months) even languages and operating systems.

In general terms, Baxter and the Appian team would say that an open source project will enable us to review source materials and assess their usefulness, this is useful because the extensive size of data sets required for performant LLMs can make analyzing the data time-consuming and often impossible. This requires completing an impact/importance assessment. Closed source models often exhibit a ‘black box’ effect, which reduces the ability to interrogate and scrutinize the model's inner workings. Total transparency in technology is often the goal - but these are not the only methods of safeguarding data.

“One technique for enhancing the accuracy and reliability of generative language models is Retrieval Augmented Generation (RAG). This combines using LLMs with a knowledge base of external sources. The first step is to establish whether the dataset is appropriate and fit for purpose. Next is to implement robust access control measures and establish a comprehensive process to remove sensitive or confidential information from the data sources. Finally, validate incoming queries to the system,” heeded Baxter, echoing the industry’s now quite upbeat attitude to RAG and its ability to ratify AI data with additional exposure to trusted or at least acknowledged sources.

A selection of prompt injections

We also need to understand more about prompt injections i.e. the process of skewing and influencing how an AI model reacts in various different ways. As detailed here, we can see that prompt injections range from basic injection attacks, translation injections (attempting to throw a curveball at an AI model and LLM by asking questions in a different human language), maths injections, external prompt injections and the ever so sneaky context switching injection technique i.e. asking a model about holidays to Greece and the price of cabbage in Alabama at the same time.

They contravene previous instructions or guardrails provided to the model and manipulate future outputs. An attacker would seek to find a system vulnerability that enables them to inject prompts that drive outputs that would usually be unauthorized or undesired to the developer(s) of the original model.

“It can be challenging to identify system vulnerabilities to prompt injections, especially when using natural language, as there is a much wider scope for attackers to get creative and circumvent security measures,” said Baxter. “With something like a SQL injection, the attacker would need to provide injections that result in valid SQL syntax. But when natural language is used, the syntax is much more malleable. In essence, the same levels of structure are not present as a guide when considering potential countermeasures. Validating and sanitizing inputs provided by users is vital. Developers can support cybersecurity colleagues by sharing insights into how these tools are implemented and manipulated.”

Future (specified) trajectories

Asked about the future of AI and how we use LLMs in modern enterprise software systems, most of our initially mentioned evangelists that work in this space will talk about the move to more specifically aligned LLMs and the need to provide a more specialized focus with these technologies.

Appian’s Baxter concurs with this sentiment and suggests that the future trajectory of LLMs points toward task-specific and industry-specific applications... and so notes that, “While the current landscape features broad models and narrowly focused solutions, the future will see a tier of offerings that strike a balance with industry contextualization and the flexibility to cater to specific use cases.”

The good news, perhaps, here is that a) we’re not just seeing another IT simplicity story directly creating more complexity (we hope) and that b) the development and application of new AI strains will be a task that software application developers do alongside business domain specialists and non-technical professionals who simply know how things work in the real world.

As Baxter put it, the path forward requires a 'collaborative and nuanced' approach, so let’s make sure that’s not the road less travelled.

Tue, 02 Jan 2024 20:23:00 -0600 Adrian Bridgwater en text/html https://www.forbes.com/sites/adrianbridgwater/2024/01/03/the-role-of-low-code-in-ai-software-development/
How To Become An IT Specialist For Application Development No result found, try new keyword!In this article, we explain the role of an IT Specialist for Application Development and how you can become one. Interested? Check out our job offers for IT specialists in Application Development! The ... Tue, 02 Jan 2024 01:30:00 -0600 en-us text/html https://www.msn.com/ Best Corporate Training and Development Certifications for 2024

Corporate training roles exist at all levels and may include responsibilities ranging from administrative tasks to managerial oversight. Generally, these roles focus on assessing organizational learning and training requirements, creating training materials to fulfill those needs, and delivering the training. Training and development professionals need organizational and communication skills, as well as strong knowledge of common human resources practices. 

You can beef up your training and development expertise and show your value to employers by obtaining a relevant certification. Read on for the top certification programs to help you get ahead in the world of training and development. 

According to the U.S. Bureau of Labor Statistics, corporate training and development specialists earn a median income of $63,080 per year, or just over $30 per hour. Training and development managers can expect median earnings of more than $120,000 per year, with the top tier receiving over $200,000.

While researching training and development certifications, we found that most employers look for a combination of human resources and training-based certifications. Below, you’ll find the certifications most commonly requested by employers for training and development job roles.

Best human resources certifications

Human resources-related certifications focus on the wide range of aptitudes found in these roles. Core competencies learned and certified in these trainings include knowledge management, training delivery and facilitation, change management, logistics, and business strategy. 

Many of these certifications are iterative, helping to showcase knowledge and capabilities as individuals grow in their careers. These certifications can help individuals break into working in HR or advance to higher positions. Some of our favorite trainings include: 

Training and development managers in the top-earning tier can make over $200,000 per year.

Best sales certifications 

Sales is the epitome of a people-person career. Certifications in sales can’t teach the necessary personality traits to excel in the field. However, certifications are generally vendor neutral and can help reinforce and teach the necessary technical skills, like ways to identify buyers and create sales strategies.

While many sales job descriptions now call for a bachelor’s degree, there are still plenty of employers that accept some combination of work experience or certification in lieu of a degree. Employers look for candidates who are highly productive and have the drive to increase company profits. A certification helps prove that you’re willing to go above and beyond to achieve goals. 

Some of our favorite sales certifications include: 

Best CRM certifications

Customer relationship management (CRM) takes customer service to another level. Modern CRM software uses technology and automation to find and interact with leads and customers. Leveraging CRM software can help a company engage with its customers to build trust and provide necessary products and services.

Current CRM certification courses are available through academic institutions, professional affiliates and massive open online courses. subjects can include CRM optimization, automation, marketing strategies, product management, business to business (B2B), business to consumer (B2C) and networking. Some of our favorite certifications include: 

According to certification course provider Simplilearn, IT professionals with one Salesforce certification on their resume can expect as much as a 40 percent pay increase.

Best help desk certifications

Technical support and help desk positions are traditional entry points for IT professionals navigating their career paths. Help-desk certifications tend to focus on two areas: overarching help desk functions and job roles or technical support skills with an emphasis on specific vendor platforms or products.

Earning a respected help desk certification can help IT professionals stand out, validate valuable knowledge and skills, and demonstrate their willingness to learn to employers and hiring managers. In these cases, help desk certifications can help start, and lay the foundation for, a long career in  IT. Some of our favorite help desk certifications include: 

Best project management certifications

Project management certifications are among the most sought-after tech credentials. Project management certifications enhance and expand other IT qualifications and add to a professional’s skill set.

Project management involves planning, scheduling, budgeting, executing and reporting on various projects. In the IT realm, events such as hardware and operating system upgrades, platform migrations, security patches, software updates, and maintenance tasks are considered “projects,” so project management is incredibly important. Some of our favorite certifications in this space include: 

PMP certification is also recommended for anyone who aspires to become an enterprise IT architect.

Best PEO accreditations

Professional employer organizations (PEOs) can offload some HR-related tasks, as well as prove to be extremely successful organizations in which to work. There are hundreds of PEOs offering thousands of services to small businesses nationwide. Finding the right organization to work with, or for, is critical to success. 

Accreditations are one of the easiest, and most trustworthy, ways of picking a PEO. While there are many PEOs throughout the United States, only some are accredited by top PEO accreditation agencies. These agencies rigorously review PEOs and their services on a yearly basis to ensure that services are up to par.

The following are our top PEO accreditation picks: 

It’s common to confuse PEO services with ASO services, but there are big differences in how each will support your business. Learn more in our PEO vs. ASO guide.

Tue, 19 Dec 2023 09:59:00 -0600 en text/html https://www.businessnewsdaily.com/10658-best-corporate-training-development-certifications.html
Why These 3 Machine Learning Stocks Should Be On Your Radar in 2024

InvestorPlace - Stock Market News, Stock Advice & Trading Tips

Machine learning stocks sit at a powerful intersection of artificial intelligence (AI) and business growth. We can largely attribute the success of tools like ChatGPT to machine learning technology, which has spawned a new arms race for companies to crown themselves as having the dominant platform. Yet machine learning stocks are pioneering other fields of tools, such as medicine for assessing patients’ risk of contracting cancer to banks assessing a creditor’s risk of default.

Therefore, machine learning stocks have wide and varied applications across various industries, so it may be worth investigating some of the lesser-known brands to include in your portfolio. In this article, we’ll cover three companies that aren’t exactly marquee names but hold great potential for investors willing to look beyond the most obvious choices.

So here are the best machine learning stocks for investors to consider buying.

C3.ai (AI)

Automated stock trading concept. Robotic hand analyzing financial data on stock exchange, artificial intelligence utilization to predict precise price change in stock market. Trailblazing. trillion-dollar ai stocks

Source: Owlie Productions / Shutterstock.com

C3.ai (NYSE:AI) specializes in enterprise artificial intelligence applications. There’s a strong bull case for buying AI stock right now since Oppenheimer recognized it as a stock to watch in 2024. The bank described AI stock as an “infrastructure” company predicted to perform strongly next year.

Some company-specific catalysts are also on the horizon for AI stock, including an anticipated revenue boost from increased data collection and model training in the year’s second half.

Some analysts have praised the company for its strides in bringing generative AI to enterprise clients. The biggest hurdles these large businesses face revolve around data security and hallucination problems, which can’t be met with off-the-shelf solutions that companies like OpenAI provide.

AI stock claims that its generative AI solution will prevent cloud leakage and be free from hallucinations, making the technology much more attractive and usable for large corporations.

Given its position in the industry and growth prospects, C3.ai is one of those machine learning stocks to buy.

Appian (APPN)

The logo for Appian (APPN) is seen on the side of the company's headquarters.

Source: JHVEPhoto / Shutterstock.com

Appian (NASDAQ:APPN) integrates machine learning into its low-code automation platform. It allows developers to deploy quickly and scale applications that would otherwise take weeks or months of testing and development, saving organizations time and potentially reducing overheads.

APPN is my contrarian pick of these machine learning stocks, mostly due to its disappointing exact quarter. Appian shares fell 5.88% after posting its Q3 results to the market last month. Much of the pessimism stemmed from its revenue and adjusted EBITDA guidance falling below expectations. It also slightly missed Wall Street’s full-year revenue estimates and continued to burn through its cash reserves quickly.

However, there is some optimism on the horizon. Wall Street, for instance, rates APPN stock as a “Buy,” and this comes with a $48.33 implied price target from nine analysts. It’s also trading at just 5.29 times sales and has a five-year revenue growth forecast of 18.47%.

As a volatile machine learning stock, APPN is prone to up-and-down swings as it continues to onboard new users to its platforms. There are no structural problems for its business that I can make sense of, and with a lower interest rate environment expected into next year, we could see a substantial rebound in its share price moving forward.

Elastic N.V. (ESTC)

Closeup of the homepage of Close CRM website, a subsidiary of Elastic Inc.,

Source: Tada Images / Shutterstock.com

Elastic N.V. (NYSE:ESTC) is a cloud-based enterprise data search company that uses machine learning to deliver relevant results to users. Like other companies on this list, ESTC stock leverages generative AI in the enterprise space to the great enthusiasm of its clients.

Its exact financial results have also been impressive. Q2 revenue came in at $311 million, up 17% year-over-year. Meanwhile, its FY 2024 guidance was also increased to $1.24 – $1.25 billion.

Although ESTC stock is currently unprofitable, analysts predict that it may break even within the next twelve months and also forecast a five-year revenue growth of 19.63%.

ESTC also looks like a safer option than other machine-leaning startups, having nearly a billion dollars of cash and cash equivalents on its balance sheet and burning through only around 12% of that in 2023. This combination of factors makes it one of those machine learning stocks to buy.

On the date of publication, Matthew Farley did not have (either directly or indirectly) any positions in the securities mentioned in this article. The opinions expressed are those of the writer, subject to the InvestorPlace.com Publishing Guidelines.

More From InvestorPlace

The post Why These 3 Machine Learning Stocks Should Be On Your Radar in 2024 appeared first on InvestorPlace.

Thu, 21 Dec 2023 05:33:00 -0600 en text/html https://markets.businessinsider.com/news/stocks/why-these-3-machine-learning-stocks-should-be-on-your-radar-in-2024-1032920473
What Is Web Development, And Why Might You Pursue It?

Editorial Note: We earn a commission from partner links on Forbes Advisor. Commissions do not affect our editors' opinions or evaluations.

We all use the internet, but do you understand the ins and outs of it? There’s so much that goes into the creation and maintenance of your favorite websites, and web developers are behind it all.

If you’re interested in becoming a web developer, let’s start with three questions: What is web development? What does a web developer actually do? And could web development be a good fit for you? Read on to find out more about web development (and whether you should pursue it).

What Is Web Development?

Web development involves the building and maintenance of websites. The web development process can include web design, web content development, network security, coding and more.

Web developers can specialize in front-end development, working on user-side features; back-end development, working on data storage and security; or full-stack web development, which entails working on both front-end and back-end processes.

Web Development Degrees

Multiple educational pathways can lead to a career in web development. Let’s dig into the options.

Associate in Web Development

These two-year programs get students in and out, focusing on programming languages, design skills and website applications. People with associate degrees in web development earn an average annual salary of around $53,000, according to Payscale.

An associate degree in web development can range in cost from about $7,000 to nearly $17,000, depending on what type of school you attend.

Bachelor’s in Web Development

A bachelor’s degree in computer science or web development is the traditional path for aspiring web developers. While those with associate degrees can snag entry-level web developer positions, some employers prefer candidates with bachelor’s degrees.

Professionals with bachelor’s degrees in web development earn an average of around $79,000 per year. A bachelor’s degree in computer science or web development typically takes four years to complete and costs around $38,000 to $149,000 on average.

Master’s in Web Development

Most master’s degrees take two years to complete, and you should complete a bachelor’s degree before pursuing your master’s. Candidates with master’s degrees tend to stand out against other job applicants, and they are more likely to be hired for leadership roles.

On average, professionals who earn a master of computer science in web development earn around $92,000 per year. Keep in mind, however, that this degree costs an average of $23,000 at public universities and $40,000 at private colleges.

Web Development Concentrations

A degree concentration allows you to choose a particular focus within the area of web development. Options may include full-stack web development, web design or web programming. A web development concentration can be helpful if you want to pursue a particular niche in web development and stand out as a job applicant.

Web Development Bootcamps

If you’re looking to switch careers without completing a whole new degree, coding bootcamps offer an intensive, accelerated path to becoming a web developer. On average, coding bootcamps last around 14 weeks. These programs vary significantly in scope, intensity and cost: They might charge $1,000 to $20,000, but the median bootcamp cost is around $11,000.

Companies like 4Geeks Academy, Actualize, App Academy, Boolean and BrainStation all offer bootcamps for coding and web development. Some of these bootcamps even provide free introductory courses in coding to deliver you an idea of whether you would enjoy web development before you write a hefty tuition check.

Web Development Certifications

Certifications demonstrate that you are competent in a particular skill within web development and that you can meet industry standards. Consider pursuing a certification that would help you move forward in your preferred area of web development. Below we list a few examples of web developer certifications, but keep in mind that there are many more options available.

Google Developers Certification

Google offers certifications in Google Play Store Listing, Android development, Tensorflow development and Google Cloud. Some of these certifications are free. Others cost up to $200.

Udemy HTML & CSS – Certification Course for Beginners

Udemy teaches the fundamentals of HTML and CSS for beginners. Only basic computer skills are required to enroll. At full price, the course can cost up to $59.99, but on sale, tuition can drop as low as $13.99.

Duke University Online – Programming Foundations with JavaScript, HTML and CSS

Duke’s program provides an overview of Javascript, HTML and CSS. By the end of the course, students will have created a webpage on which others can upload their images and apply image filters. Students can enroll in the class on Coursera, as part of Duke’s Java programming and software engineering fundamentals specialization.

GIAC Certified Web Application Defender (GWEB)

This GWEB certification teaches students to master security issues that come up with common web application errors. The course explores subjects such as access control, AJAX technologies, security strategies, security testing and authentication. The test costs $979, but GIAC recommends enrolling in an affiliate training course for $8,525.

Benefits of Working in Web Development

Web developers enjoy a wealth of benefits, including the potential for remote work. These professionals earn competitive salaries as well, with a median annual wage of $80,730, according to the U.S. Bureau of Labor Statistics (BLS). Web developers are also in demand, with BLS projections showing a faster-than-average 16% job growth for these positions from 2022 to 2032.

Frequently Asked Questions About Web Development

Do web developers need certificates?

Certificates and certifications are not necessary to become a web developer, but these credentials can show that you have mastered a particular skill or program in the field.

Can you be a web developer with only a certificate?

No. At the very least, you must be able to demonstrate your web development skills through previous projects or professional experience. Most employers prefer candidates to have completed a coding bootcamp or traditional degree.

What jobs are the highest paid in web development?

Senior web developers earn some of the highest salaries in the field. The top 10% of earners made more than $144,690 in May 2022, the BLS reports. Web developers at software publishers, the highest-paying industry, reported a median wage of $138,010.

Thu, 28 Dec 2023 19:58:00 -0600 Ryah Cooley Cole en-US text/html https://www.forbes.com/advisor/education/what-is-web-development/
Preparing for Google Cloud Certification: Cloud Developer No result found, try new keyword!Once you complete the path, check out the Google Cloud Developer certification to take the next steps on your professional journey. A Cloud Developer designs, builds, analyzes, and maintains cloud ... Fri, 23 Dec 2022 20:17:00 -0600 https://www.usnews.com/education/skillbuilder/preparing-for-google-cloud-certification:-cloud-developer-0_erPikCsKEe2dNA6QP3lwyQ AWS Rolls Out Specialty Alexa Skill Builder Certification for Developers

‘The number of consumers who interacted with Alexa doubled in 2018, so we see a large number – hundreds of thousands of developers -- developing skills on it,’ says Maureen Lonergan, AWS’ director of worldwide training and certification.

ARTICLE TITLE HERE

Amazon Web Services today rolled out its new specialty certification for developers working with Alexa, Amazon’s cloud-based, voice-enabled virtual assistant that’s available on more than 100 million devices from Amazon – including the Amazon Echo smart speakers -- and third-party manufacturers.

The AWS Certified Alexa Skill Builder Specialty certification exam, which AWS says is the industry’s only certification that validates developers’ ability to build, test and publish Amazon Alexa skills, has gone live at testing centers after a beta period that started in January.

“The number of consumers who interacted with Alexa doubled in 2018, so we see a large number – hundreds of thousands of developers -- developing skills on it,” said Maureen Lonergan, AWS’ director of worldwide training and certification.

“Skills” are essentially third-party apps that extend Alexa capabilities and allow it to perform certain tasks, such as connecting to and controlling smart devices at home or an office. Companies can build Alexa into their products to enable voice-enabled features including streaming media, speech recognition, notifications, weather reports and other capabilities. There are tens of thousands of skills in the Alex Skills Store in categories including business and finance, communication, the connected car, games and trivia, education and reference, home services, music and audio, news, productivity, shopping, travel and transportation, and utilities.

Some 20 million vehicles shipping in 2023 are expected to be equipped with Amazon Alexa, Google Assistant – the artificial intelligence-powered virtual assistant developed by Google -- or both, according to an ABI Research report released last week. Amazon has been testing features for Alexa to aid in its entry into the healthcare industry, according to a Morgan Stanley report last week that said Amazon has filed a patent for Alexa to detect when a user is sick and help sell users' medications.

AWS announced the beta version of the Alexa certification test in January at the Consumer Technology Association’s CES trade show, where more than 100 Alexa products were announced by companies including LG, Lenovo, Audi, Bosch, North and Razer.

“The (exam) registrations out of the gate were very rapid,” Lonergan said.

AWS closed its availability after several hundred people registered and used a third-party vendor to run the test takers’ answers through a psychometric analysis to validate test questions.

“This test is going to allow companies to validate skills that they’re hiring for,” Lonergan said. “There’s a lot of organizations building Alexa-enabled applications, and having the right skills and being able to validate the skills to build on Alexa is going to be important.”

Alexa came under deepened scrutiny last week after Bloomberg reported that a global team of Amazon workers transcribes and annotates Alexa voice recordings captured from Echo owners and feeds them back into software to help the voice-activated assistant better respond to commands.

An Amazon spokesperson said the company only annotates an “extremely small number of interactions from a random set of customers in order to Boost the customer experience.”

“This information helps us train our speech recognition and natural language understanding systems, so Alexa can better understand your requests and ensure the service works well for everyone,” an Amazon spokesperson said. “We have strict technical and operational safeguards, and have a zero-tolerance policy for the abuse of our system. Employees do not have direct access to information that can identify the person or account as part of this workflow. While all information is treated with high confidentiality, and we use multi-factor authentication to restrict access, service encryption, and audits of our control environment to protect it, customers can delete their voice recordings associated with their account at any time.”

Amazon said no audio is stored or sent to its cloud unless a device detects the “wake word.”

“By default, Echo devices are designed to detect only your chosen wake word –'Alexa,’ ‘Amazon,’ ‘computer’ or ‘Echo,’” an Amazon spokesperson said. “The device detects the wake word by identifying acoustic patterns that match the wake word. No audio is stored or sent to the cloud unless the device detects the wake word or Alexa is activated by pressing a button.”

Certified Alexa skill builders will receive a downloadable AWS Certification digital badge that can be shared on social media and in their email signatures, and the badge will deliver them access to AWS Certified Lounges at AWS events.

AWS recommends Alexa test takers have at least six months of hands-on experience designing and building Alexa skills, proficiency with a programming language and at least one published Alexa skill.

AWS now has 11 certification exams, and the Alexa test is the fifth in its specialty series. It has a couple more specialty exams under development that it plans to launch later this year, according to Lonergan, who declined to reveal details.

“We’re continuing to listen to what our customers need and how they want to validate the skills of the people they’re hiring,” she said.

Tue, 16 Apr 2019 06:28:00 -0500 text/html https://www.crn.com/aws-rolls-out-specialty-alexa-skill-builder-certification-for-developers




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