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Transforming PPC Reporting with AI

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PPC Reporting: From Frustration to Opportunity with AI

1. Collect Complete And High-Quality PPC Data

We need data to guide us before we can optimize accounts and share our wins, so let’s start there.

The Problems With Data Before AI

Inconsistent and missing data plague PPC efforts.

Google, Meta, Microsoft, and Amazon operate in their own silos, each taking credit for all conversions that have any touchpoint with their platforms. This leads to double counting, making it difficult to decide where to allocate budgets for optimal results.

In other words, the data between the various ad platforms is inconsistent. Specifically, the conversion value advertisers see in their business data may be lower than the sum of all conversion values reported by the ad platforms.

Add to this the challenge of missing data. Privacy regulations like GDPR and Apple’s iOS changes limit tracking capabilities, which causes data loss, incomplete conversion paths, and gaps in attribution.

AI-Driven Solutions For Data Hygiene And Compliance

1. Data Clean Rooms And Privacy-First Measurement

Clean rooms like Amazon Marketing Cloud (AMC) and Google Ads Data Hub allow advertisers to securely analyze anonymized cross-channel performance data without violating privacy laws.

These platforms aggregate data from multiple sources, giving marketers a comprehensive view of the customer journey.

2. Modeled Conversions

While clean rooms are great for unifying cross-platform data, their usefulness is predicated on data completeness.

When privacy regulations make it impossible to get all the data, clean rooms like Google Ads Data Hub and Amazon Marketing Cloud use AI-powered modeled conversions to estimate user journeys that can’t be fully tracked.

3. Server-Side Tagging And First-Party Data Integration

Server-side tagging lets marketers control data collection on their servers, bypassing cookie restrictions.

Platforms like Google Tag Manager now support server-side implementations that improve tracking accuracy while maintaining privacy compliance.

3. Advanced Statistical Analysis Available To Anyone

Before AI advancements, conducting a statistical analysis could be a labor-intensive process requiring specialized software or data science expertise.

But today, generative AI enables marketers to explore these areas that were previously firmly outside their realm of expertise.

How AI Automates Seasonal Analysis

In one of my PPC Town Hall podcast episodes, Cory Lindholm demonstrated how GPT can handle complex seasonality analysis in minutes.

Inspired by this, I used GPT’s Advanced Data Analysis feature to upload weekly Google Ads data and run a full decomposition.

2. Communicate Results Effectively Across Teams

With solid data in place and AI-fueled ways to speed up analysis, we should have some great results to share with stakeholders.

But sharing results through reports has traditionally been one of the most time-consuming and least loved tasks that fall on the plate of the typical account manager. And there were other problems, too.

The Problem With Sharing Reports Before AI

Reports were often static, one-size-fits-all documents that failed to meet the needs of different stakeholders.

AI Solutions For Tailored Reporting

1. LLM Report Summarization

LLMs like Claude, Gemini, and ChatGPT can quickly generate different explanations of reports from the same underlying data, enabling efficient customization for each audience.

2. Interactive Dashboards For Real-Time Transparency

AI-driven dashboards provide live, customizable views of campaign performance. Stakeholders can explore data interactively, filtering by date ranges, platforms, or key performance indicators (KPIs), reducing the need for frequent manual report updates.

Actionable Tips:

  • Set up custom GPTs for every client you work with.
  • Implement reporting tools that use natural language to explore the data.

Conclusion: From Reporting To Strategic Decision-Making With Generative AI

Generative AI has redefined PPC reporting, transforming a once fragmented and time-consuming process into a streamlined, insight-driven workflow.

It doesn’t just automate data collection and report generation; it also surfaces hidden trends, correlations, and anomalies that might otherwise go unnoticed.

This enables marketers to make smarter, faster, and more strategic decisions based on real-time insights.

With AI-driven tools, marketers can see beyond surface-level metrics, discovering patterns and opportunities that traditional reporting might take hours or days to uncover.

This improved understanding of performance empowers teams to refine budget allocation, creative strategy, and campaign targeting more effectively, leading to more substantial outcomes and greater profitability.

The conclusion is simple. With Generative AI, PPC managers have more complete data, leading to better insights and better decisions – all of which can be shared more meaningfully with all involved stakeholders.

More Resources:

Featured Image: Igor Link/Shutterstock

Integrating Cypress with Jenkins API for Automated Test Preparation

Automating Pre-Test Jobs with Jenkins API

Automating Pre-Test Jobs with Jenkins API

When performing automated tests in Cypress, you often need to prepare data or bring the application to a certain state before execution. This can involve seeding a database, generating test data, or performing backend tasks.

Automating Pre-Test Jobs with Jenkins API

To incorporate Jenkins jobs into Cypress, we use the Jenkins API to start a job and wait for its completion. Let’s define some custom Cypress commands to handle this.

Starting a Jenkins Job

We begin by defining a general function to start a Jenkins job:

const JENKINS_URL = '{your_jenkins_url}';
const JOB_NAME = 'Console script runner (dev-beta)';
const API_TOKEN = '{your_jenkins_api_token}';
function startJenkinsJob(project, script, wait) {
  const url = `http://${JENKINS_URL}/job/${JOB_NAME}/buildWithParameters?token=${API_TOKEN}&PROJECT=${project}&ENVIRONMENT=beta&CONSOLE_SCRIPT=${script}`;
  cy.request({
    method: 'GET',
    url,
    failOnStatusCode: false,
  }).then((response) => {
    if (wait) {
      const locationParts = response.headers.location.split('/');
      const queueId = locationParts.slice(-2, -1)[0];
      cy.waitForBuildNumber(queueId);
    }
  });
}

Implementing Specific Jenkins Commands

With these general functions in place, we can define specific commands. For example, to clear a cache before running tests:

Cypress.Commands.add('clearCache', (country, wait) => {
  return startJenkinsJob('my_project', 'cache/flush-all country=' + country, wait);
});

Using Jenkins Jobs in Cypress Tests

Now, let’s implement our cache-clearing command in a test:

describe('Test with cleared cache', () => {
  before(() => {
    const countryId = Cypress.env().countryId;
    cy.task('log', `Clearing cache on ${countryId}`);
    cy.clearCache(countryId, true);
  });

  it('Your test...', () => {
    // Your test code
  });
});

Expanding Possibilities for Automated Testing

Integrating Cypress with Jenkins API opens up many new possibilities:

  • Automatically setting up test environments.
  • Running backend processes before tests.
  • Ensuring data consistency before executing test cases.

With this approach, we eliminate the need for manual job execution, making our test automation more robust and reliable.

Conclusion

What other pre-test tasks would you automate with this method? Let’s discuss in the comments!

FAQs

  1. How do I integrate my Jenkins job with Cypress?

    Use the Jenkins API to start a job and wait for its completion, as demonstrated in the article.

  2. What are some use cases for automating pre-test jobs?

    Examples include automatically setting up test environments, running backend processes before tests, and ensuring data consistency before executing test cases.

  3. How do I implement specific Jenkins commands in my Cypress tests?

    Use the `add` method of the Cypress Commands class to define custom commands, as shown in the article.

VAST Fleshes Out Data Platform for Enterprise RAG Use Cases

VAST Data Unveils Major Update to Its Platform, Enabling Exabyte-Scale AI Workloads

VAST Data is quietly assembling a single unified platform capable of handling a range of HPC, advanced analytics, and big data use cases. Today, it unveiled a major update to its VAST Data Platform engine aimed at enabling enterprises to run retrieval augmented generation (RAG) AI workloads at exabyte scale.

A New Approach to Data Storage

When solid-state drives went mainstream and NVMe over Fabric was invented nearly a decade ago, the folks who founded VAST Data sensed an opportunity to rearchitect data storage for high-performance computing (HPC) at the exabyte level. Instead of trying to scale existing cloud-based platforms into the HPC realm, they decided to take a clean-sheet approach via DASE, which stands for Disaggregated and Shared Everything.

New Capabilities

The first element of the new DASE approach with VAST Data Platform was the VAST DataStore, which provides massively scalable object and file storage for structured and unstructured data. That was followed up with DataBase, which functions as a table store, providing data lakehouse functionality similar to Apache Iceberg. The DataEngine provides the capability to execute functions on the data, while the DataSpace provides a global namespace for storing, retrieving, and processing data from the cloud to the edge.

InsightEngine and Beyond

In October, VAST Data unveiled the InsightEngine, which is the first new application designed to run atop the company’s data platform. InsightEngine utilizes Nvidia Inference Microservices (NIMs) from Nvidia to be able to trigger certain actions when data hits the platform. Then, a few weeks ago, VAST Data bolstered those existing capabilities with support for block storage and real-time event streaming via an Apache Kafka-compatible API.

New Features

Today, VAST Data bolstered the VAST Data platform with three new capabilities, including:

  • Vector Search and Retrieval: Enables customers to store and query vectors at exabyte scale, eliminating the need for separate vector databases.
  • Serverless Triggers and Functions: Allows customers to trigger functions and events on data as it is ingested into the platform.
  • Fine-Grained Access Control: Provides row- and column-level permissions for secure data management and governance.

Conclusion

VAST Data’s platform is designed to help enterprises unlock their data without having to give it away to model builders or fine-tune models. With the new capabilities, customers can consolidate their data, scale their AI workloads, and ensure secure data management and governance.

Frequently Asked Questions

Q: What is VAST Data’s platform?
A: VAST Data’s platform is a unified platform for HPC, advanced analytics, and big data use cases.

Q: What is the DASE approach?
A: DASE stands for Disaggregated and Shared Everything, a clean-sheet approach to rearchitect data storage for high-performance computing (HPC) at the exabyte level.

Q: What are the new capabilities announced today?
A: Vector search and retrieval, serverless triggers and functions, and fine-grained access control are the new capabilities announced today.

The Unbeatable Bottle Campaign

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The Enduring Power of Print Advertising: Absolut’s Iconic Campaign

The Longest-Running Print Ad Campaign

In today’s digital landscape, print advertising is often declared defunct. However, rumors of the format’s death have been greatly exaggerated. Some of today’s most iconic ads show no sign of the dreaded "pivot to video" – and perhaps the most iconic campaign of all is also the longest running.

The Absolut Story

A Absolut Vodka has produced over 2,000 variations of its "bottle" ad since 1980, in the perfect advertising encapsulation of the phrase, "If it ain’t broke…" And through sheer repetition, it managed to turn what could have been a one-hit wonder into one of the best print ad campaigns ever.

The Unique Bottle Design

The key to Absolut’s success lies in its unique straight bottle design, which has remained unchanged since its inception. Deb Dasgupta, Global VP of Marketing for Absolut, believes that this design is what makes the brand’s ads unique. "I think it’s so pure, it’s so simple, which also makes it a canvas for creativity and imagination, and also because the purity and transparency of the liquid in it. We’ve done so many limited editions and powerful collaborations using the bottle. Now there are so many bringing back heritage assets. But for us, it’s been there all along – we never got rid of it."

A Canvas for Creativity

The bottle’s simplicity has allowed for endless creativity and imagination, resulting in over 2,000 variations of the ad. From city-based designs for London and New York to collaborations with artists like Andy Warhol, the possibilities are endless. You can view every version of the ad ever made on the Absolut website.

Conclusion

The success of Absolut’s campaign is a testament to the power of print advertising. Despite the rise of digital media, the brand has managed to maintain its iconic status through sheer creativity and repetition. The unique bottle design has become synonymous with the brand, and its simplicity has allowed for endless variations and collaborations.

Frequently Asked Questions

Q: How many variations of the Absolut ad have been created?
A: Over 2,000

Q: How long has the Absolut campaign been running?
A: Since 1980

Q: What is the key to the campaign’s success?
A: The unique straight bottle design, which has remained unchanged since its inception.

Q: How can I view all the variations of the ad?
A: You can view every version of the ad ever made on the Absolut website.

Nvidia’s AI Empire: A Look at Its Top Startup Investments

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The Billion-Dollar-Round Club

No company has capitalized on the AI revolution more dramatically than Nvidia. Its revenue, profitability, and cash reserves have skyrocketed since the introduction of ChatGPT over two years ago — and the many competitive generative AI services that have launched since. And its stock price soared.

The Goal of Corporate Investing

Nvidia has stated that the goal of its corporate investing is to expand the AI ecosystem by backing startups it considers to be “game changers and market makers.”

The Billion-Dollar-Round Club

  • OpenAI: Nvidia backed the ChatGPT maker for the first time in October, reportedly writing a $100 million check toward a colossal $6.6 billion round that valued the company at $157 billion. The chipmaker’s investment was dwarfed by OpenAI’s other backers, notably Thrive, which according to the New York Times invested $1.3 billion.
  • xAI: Nvidia participated in the $6 billion round of Elon Musk’s xAI. The deal revealed that not all of OpenAI’s investors followed its request to refrain from backing any of its direct competitors. After investing in the ChatGPT maker in October, Nvidia joined xAI’s cap table a few months later.
  • Inflection: One of Nvidia’s first significant AI investments also had one of the most unusual outcomes. In June 2023, Nvidia was one of several lead investors in Inflection’s $1.3 billion round, a company founded by Mustafa Suleyman, who earlier founded DeepMind. Less than a year later, Microsoft hired Inflection AI’s founders, paying $620 million for a non-exclusive technology license, leaving the company with a significantly diminished workforce and a less defined future.
  • Wayve: In May, Nvidia participated in a $1.05 billion round for the U.K.-based startup, which is developing a self-learning system for autonomous driving. The company is testing its vehicles in the U.K. and the San Francisco Bay Area.

The Many-Hundreds-of-Millions-of-Dollars Club

  • Crusoe: A startup building data centers reportedly to be leased to Oracle, Microsoft, and OpenAI raised $686 million in late November, according to an SEC filing. The investment was led by Founders Fund, and the long list of other investors included Nvidia.
  • Figure AI: In February 2024, AI robotics startup Figure raised a $675 million Series B from Nvidia, OpenAI Startup Fund, Microsoft, and others. The round valued the company at $2.6 billion.
  • Mistral AI: Nvidia invested in Mistral for the second time when the French-based large language model developer raised a $640 million Series B at a $6 billion valuation in June.
  • Lambda: AI cloud provider Lambda, which provides services for model training, raised a $480 million Series D at a reported $2.5 billion valuation in February. The round was co-led by SGW and Andra Capital Lambda, and joined by Nvidia, ARK Invest, and others. A significant part of Lambda’s business involves renting servers powered by Nvidia’s GPUs.
  • Cohere: In June, Nvidia invested in Cohere’s $500 million round, a large language model provider serving enterprises. The chipmaker first backed the Toronto-based startup in 2023.
  • Perplexity: Nvidia first invested in Perplexity in November of 2023 and has participated in every subsequent round of the AI search engine startup, including the $500 million round in December, which values the company at $9 billion, according to PitchBook data.

Deals of Over a $100 Million

  • Ayar Labs: In December, Nvidia invested in the $155 million round of Ayar Labs, a company developing optical interconnects to improve AI compute and power efficiency. This was the third time Nvidia backed the startup.
  • Kore.ai: The startup developing enterprise-focused AI chatbots raised $150 million in December of 2023. In addition to Nvidia, investors participating in the funding included FTV Capital, Vistara Growth, and Sweetwater Private Equity.
  • Hippocratic AI: This startup, which is developing large language models for healthcare, announced in January that it raised a $141 million Series B at a valuation of $1.64 billion led by Kleiner Perkins. Nvidia participated in the round, along with returning investors Andreessen Horowitz, General Catalyst, and others. The company claims that its AI solutions can handle non-diagnostic patient-facing tasks such as pre-operating procedures, remote patient monitoring, and appointment preparation.

Conclusion

Nvidia has been at the forefront of the AI revolution, and its investments in AI startups have been instrumental in shaping the industry. The company has participated in numerous funding rounds, investing in startups that are developing cutting-edge AI technologies.

FAQs

Q: What is Nvidia’s goal with its corporate investing?
A: Nvidia’s goal is to expand the AI ecosystem by backing startups it considers to be "game changers and market makers."

Q: How much has Nvidia invested in AI startups?
A: According to PitchBook data, Nvidia has participated in 49 funding rounds for AI companies in 2024, a significant increase from the previous year.

Q: Which AI startups has Nvidia invested in?
A: Nvidia has invested in numerous AI startups, including OpenAI, xAI, Inflection, Wayve, and many others.

Q: What is the total value of Nvidia’s investments in AI startups?
A: The total value of Nvidia’s investments in AI startups is not publicly disclosed, but it is likely in the billions of dollars.

In the Future, Fewer Real Artists Like Me

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The Artist is Valuable

Stanley ‘Artgerm’ Lau is one of the most established comic artists working today, having worked for Marvel, DC Comics, and game publishers such as Capcom and Square Enix. However, the rise in popularity of the best AI art generators has kept the debate around whether AI is good, bad, or workable for artists a constant discourse.

AI is Not Art

For Stanley, AI and its uses in art is a straightforward one – AI isn’t art, it can’t make art, and it isn’t creative. "I don’t agree that AI images are art,” Stanley states firmly. “I don’t consider them art because art is exclusively a human endeavour. You need to have a person who interacts and interprets the world through a very specific visual lens and then transforms that into art. That must be done by a human."

The Importance of Human Touch

Stanley sees a crucial distinction between AI as a tool in the creative process and AI as a replacement for human artistry. While he acknowledges the practical uses of AI in industries like animation and game development, he warns against mistaking AI-generated images for genuine artistic expression.

"It makes sense for companies to use AI to ease development – like animators using AI to fill in frames – but the final product should still have a human touch," he reflects.

The Artist’s Legacy

For Stanley, an artwork’s value is not just in the image itself but in the artist’s lived experiences and creative vision. "When people buy my work, they don’t just buy the image. They buy my legacy, my experience in life. They’re purchasing a piece of my life – that’s what gives it value," he reflects.

The Future of Art

Stanley compares AI-generated art to mass-produced goods: "In the past, many products were handmade – shoes, clothing, bags. Then machines took over. Now, if you want something handmade, you have to pay a premium. I believe the same will happen with art. AI-generated images will flood the market, but people will eventually return to valuing human-made art."

The Impact on Aspiring Artists

One of Stanley’s biggest concerns is how AI affects aspiring artists, especially those trying to break into the industry. "In my own circle, I see how AI is replacing roles." he says, adding: "In advertising, for example, there used to be visualisers who would create concept sketches. Now, AI can generate a visual brief instantly, reducing the need for those jobs."

Maestro and Servant

He doesn’t dismiss AI entirely, recognising that artists can mix the technology into their workflow, but he cautions against over-reliance. Stanley says: "Either the visualiser loses their job, or they have to adapt by learning AI tools. That’s fair, but artists must ask themselves, ‘are you driving the technology, or is the technology driving you?’ The relationship should always be that of master and servant. The artist should be in control, not the AI."

Conclusion

In conclusion, Stanley ‘Artgerm’ Lau believes that true artistry will remain a human pursuit, and using AI is not something that appeals to him. "If I ever incorporate AI into my work, I’ll forever be branded as an AI artist – there’s no way out. I’d rather preserve human creativity than succumb to the convenience of AI-generated shortcuts."

FAQs

Q: What do you think about AI-generated art?
A: I don’t consider AI-generated images as art because art is exclusively a human endeavour.

Q: How do you see the future of art evolving?
A: I believe that AI-generated images will flood the market, but people will eventually return to valuing human-made art.

Q: How do you think AI affects aspiring artists?
A: AI is replacing roles, and artists must adapt by learning AI tools or risk losing their job.

Q: What advice would you give to aspiring artists?
A: The most interesting part of art is the process – solving problems, creating something from nothing – so why would you outsource the most fun part of the creative journey to a machine?

Q: Will you ever incorporate AI into your work?
A: I wouldn’t want to be branded as an AI artist; I’d rather preserve human creativity.

5 Ways to Boost Your Team’s Productivity

5 Ways to Make Your Teams More Productive Without Relying on Generative AI

The experts suggest that generative AI’s game-changing capabilities mean we won’t have to focus on mundane tasks that limit our productivity. However, while the technology has benefits, generative AI also comes with challenges, such as ethical risks and hallucinations.

Various business leaders have told ZDNET that keeping humans in the loop is the key to the successful deployment of AI. Talented professionals ensure emerging technology behaves as it continues to evolve.

So, with humans expected to fulfill an important role in a workplace boosted by generative AI, how can managers ensure their staff are eager and productive? Five business leaders gave us their best-practice tips.

1. Make Your Team Feel Empowered

Carrie Jordan, global director of proposals at Microsoft, said a solid culture is the key to creating more productive teams.

"I believe that to create the best team in the world, you have to create the best team to work for," she said.

"In my experience, when your team feels valued, they feel known as a person first, you celebrate their unique characteristics and recognize them, and you encourage collaboration and create a safe psychological space in the team, then they will naturally want to rise and be high performers for you."

2. Stop Having Pointless Meetings

Madoc Batters, head of cloud and IT security at Warner Leisure Hotels, said he boosts productivity using Agile development techniques.

"We’re big believers in using extreme programming, running sprints, doing Kanban sessions, and applying all the artifacts for Agile workflows," he said.

Batters told ZDNET he likes to make work processes visible so everybody knows what tasks they should be doing. Once people have direction, you can stop attending pointless get-togethers.

3. Focus on What Makes People Happy

Bev White, CEO at recruiter Nash Squared, said managers must treat each person in their team individually:

"We’re all different and different things make us tick," she said.

White told ZDNET that employees are more productive when they’re happier. Focus on your staff’s happy places and help them reach those destinations.

4. Give Staff Regular Feedback

Louisa Latham, senior business advisor at management and technology consulting firm BearingPoint, said improving productivity in team environments is a collective effort.

"Despite advances in AI, the human factor remains crucial," she said.

Latham told ZDNET that regular team reviews that score professionals against targets can help managers unlock continuous productivity improvements.

5. Replicate the Best Techniques

Chris Kronenthal, president and CTO at FreedomPay, said the key to boosting productivity is working out who has the best techniques using quantitative data.

"You can still measure most things," he said. "And as soon as you start measuring, you’ll be able to discern who in the organization does things well and expeditiously and who doesn’t."

Conclusion

While generative AI has its benefits, it’s essential to remember that humans are still crucial in the deployment of AI. By following these five best-practice tips, managers can ensure their staff are eager and productive, even without relying on generative AI.

FAQs

Q: What is the key to creating a productive team?
A: A solid culture is the key to creating more productive teams.

Q: How can I stop having pointless meetings?
A: Make work processes visible, and once people have direction, stop attending pointless get-togethers.

Q: What makes people happy at work?
A: Different things make people happy, such as flexibility, development and training, recognition, and regular feedback.

Q: How can I improve productivity in my team?
A: Regular team reviews that score professionals against targets can help managers unlock continuous productivity improvements.

Q: How can I boost my team’s productivity without relying on generative AI?
A: Focus on what makes people happy, give staff regular feedback, replicate the best techniques, and keep humans in the loop.

Crafting a Hero

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The Art of 3D Character Creation: A Step-by-Step Guide

01. Creating a PureRef File

Before starting the 3D modeling process, it’s essential to create a PureRef file, a collection of reference images that will inspire and guide your project. These images can include clothing, head, female anatomy, and props that will help you set a course and save time. Every good 3D artist has their own collection of references.

02. Building the Blockout

To begin building the blockout, you can start with a sculpture from scratch or use a ready-made base mesh and modify it to fit the proportions of your concept. In ZBrush, I mainly use the Move brush, ClayBuildup to build shapes, Dam Standard to create depressions and folds, and Flatten for flat sections. It’s also crucial to use simple shapes, such as a belt being a cylinder and a head being a sphere.

03. Using DynaMesh and ZRemesher

To pose a character, you can either use a rigging system or employ a quicker process in ZBrush. I prefer the latter, using masks and the Gizmo tool to establish a pose, and then refining it with the Move brush if needed. It’s essential to pay attention to the fingers, shoulders, and pelvic alignment, as well as eye direction and head tilt adjustments. References will help you get this spot on.

04. [Insert next step…

10. Rendering Your Image

To render your image, I recommend using Marmoset Toolbag, although you can also use other rendering software like Blender. Start by uploading your model to Marmoset and adjust the scale if necessary. Arrange each material in order, taking into account the differences from Substance 3D Painter, since a different HDR format is used. It’s also useful to emphasize the silhouette, which can be done with an outline.

11. Setting-up the Lighting

To set up lighting, you can experiment with different lighting setups and techniques to achieve the desired atmosphere. For example, soft, indirect lighting can create a magical ambiance, while harsh, directional lighting can produce a dramatic effect. I use a standard setup with three light sources: a main source, one auxiliary light on the side, and a contour backlight behind the model. Experiment with the direction and power of each light source, and you can see how each works individually. In some areas, the lighting may not be enough, so you can add small light sources, but don’t overdo it.

12. Making Amendments in Post-processing

Once the lighting is suitable, render images from different angles and build a video. During post-processing, you can add effects such as a vignette, blurring, and sharpening. You can also play with camera settings to enhance the visual impact and storytelling of your render. Apply composition principles like the rule of thirds, leading lines, and depth of field to enhance the visual impact and storytelling of your render.

Conclusion

In this tutorial, we’ve explored the process of creating a 3D character model using ZBrush. From creating a PureRef file to setting up lighting and post-processing, we’ve covered the essential steps to bring your character to life. Remember to always pay attention to detail, use references, and experiment with different techniques to achieve the desired result.

FAQs

Q: What is ZBrush and how is it used in 3D modeling?
A: ZBrush is a digital painting and 3D modeling software used to create detailed, high-resolution textures and 3D models. It’s commonly used in the film, television, and video game industries.

Q: How do I create a PureRef file?
A: A PureRef file is a collection of reference images that inspire and guide your project. You can create one by collecting images of clothing, head, female anatomy, and props that will help you set a course and save time.

Q: What are some tips for posing a character in ZBrush?
A: To pose a character, you can either use a rigging system or employ a quicker process in ZBrush. Use masks and the Gizmo tool to establish a pose, and then refine it with the Move brush if needed. Pay attention to the fingers, shoulders, and pelvic alignment, as well as eye direction and head tilt adjustments. References will help you get this spot on.

Angry Miao’s Infinity Mouse

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Angry Miao’s Ridiculous, Over-the-Top Gaming Mouse is Actually Kind of Amazing

The AM Infinity Mouse has a skeletonized magnesium-alloy shell that weighs just 49 grams, making it one of the lightest full-size mice on the market. Within its hollowed-out, super lightweight black chassis is a magnetic battery that can be popped out and swapped in seconds. A spare is kept charged and at the ready on the mouse’s 2.4GHz receiver. This functionality gives the mouse its name, as Angry Miao claims hot-swapping equals "infinite" battery life.

Features

  • 8,000Hz polling rate for minimal input latency, even with high-refresh monitors
  • PixArt PAW3950 optical sensor with 30,000 DPI sensitivity
  • TTC Orange Dot Optical V2 micro switches with tactile click and sensitive registration
  • Forward and back buttons on the left side are see-through blue in this pre-production model, but will be black on final units expected to ship in June
  • 2.4GHz connectivity enabled through its RGB-illuminated dongle/battery charger
  • Support for Bluetooth and wired USB-C
  • Estimated battery life of up to 17 hours of continuous use at 8,000Hz polling, or up to 43 hours at 1,000Hz

Design and Ergonomics

The open design of the Infinity Mouse may not be to everyone’s liking, especially if you don’t want to deal with dust buildup on your mouse’s circuitry. While plenty of other mice have had cutouts for the sake of weight savings, they’re usually much more conservative honeycomb patterns. The Infinity Mouse leaves just the bare minimum of metal exposed.

However, like a race car, the Infinity Mouse may not comfortably accommodate everyone. My average hands feel perfectly fine gripping the Infinity Mouse, but none of my fingers or palm touch points fall directly on an edge. If you have small hands and rest your palm harder on the base of your mouse, you may feel differently about this one’s comfort.

Conclusion

I love this thing. Like Angry Miao’s keyboards, it’s a striking design piece to have on your desk. But unlike its boutique mechs, the Infinity Mouse is priced much more logically. I’m no esports competitor, but I’ve used my share of quality gaming mice from the likes of Logitech, Razer, and SteelSeries — and I regularly use an older Logitech G Pro Wireless.

The Infinity Mouse has great tactile click sounds, it feels snappy and solid, and its movements on a desk mat are nice and smooth. It makes my 80g Logitech feel a little hefty by comparison, and its swappable batteries are a treat. I never have to worry about pulling a cable out to clutter up my desk while the mouse charges.

FAQs

Q: Is the Infinity Mouse worth the price?
A: Yes, if you value its unique design, snappy performance, and convenient battery management.

Q: Is the Infinity Mouse right for me?
A: If you have average-sized hands and don’t mind the open design, it might be a great fit. If you have small hands or prefer a more traditional mouse shape, you might want to look elsewhere.

Q: Can I use the Infinity Mouse with my current setup?
A: Yes, it’s compatible with most gaming surfaces and mice, including my Logitech G Pro Wireless.

Q: Are the batteries really swappable?
A: Yes, simply pop out the current battery and insert a fresh one.

This accidentally raunchy religious poster is my favourite design fail ever

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A Hilarious Graphic Design Fail: The "S.F.X" Saint Francis Xavier Poster Debacle

A Unfortunate yet Amusing Mistake

Sometimes, the internet blesses us with a graphic design fail so unfortunate that it makes me question, "Surely that can’t be an accident?" One such case is a recent Instagram post from Gonzaga University students promoting Lives of the Saints, a weekly event to discuss the JPII Fellowship’s favorite religious figures. All was well until the most recent Saint of the Week poster dropped featuring prolific Jesuit missionary St. Francis Xavier.

The Design Disaster

While the series of poster designs is surprisingly slick, the creative formula hit a hitch when faced with the initials "S.F.X" and an unfortunately placed St. Francis (I’m sure you can work it out). Thanks to the design’s amusing and unsaintly new interpretation, it caught the attention of Redditors who reveled in the amusement.

The Internet Reacts

Taking to the r/graphic_design subreddit, users weighed in on the hilarious misstep. One Redditor wrote, "I dunno. Think they nailed it. I’m gonna give ol’ Francis a Google now." Another chimed in, "Ah but it gets your attention! I’d call it a successful design," while a fellow user praised the poster, writing: "100% intentional. Meant to grab the eye. Great design."

A Happy Accident or Virality Attempt?

Given the JPII Fellowship’s exclusivity, I’d say this is a hilarious happy accident rather than a stab at virality (although I do hope it has inadvertently upped attendance at Lives of the Saints). Whether it’s intentional or not, this creative mishap is a humble reminder to always get a second opinion, but as design fails go, this is without a doubt my favorite of all time.

Conclusion

This design fail is a great reminder to always double-check our work and get a second opinion. But let’s be honest, it’s also a fun reminder that even the best of us can make mistakes. And who knows, maybe this unintentional design fail will bring in more attendees to the Lives of the Saints event.

Frequently Asked Questions

Q: Is the design intentional?
A: The internet is divided on this, but it’s unclear whether the design was meant to be humorous or an actual mistake.

Q: Is this a successful design?
A: While the design may not be perfect, it’s certainly gotten attention and sparked conversation.

Q: Will this up attendance at Lives of the Saints?
A: While it’s unclear, the design has certainly generated buzz and may inadvertently attract more attendees.