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The road to the simulation point, a talk with Rizwan Virk

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What is real? That depends on who you ask. Some people will say anything you can touch and feel, make an impact on, is real. Then there are those who believe that what you experience is reality. In the Allegory of the Cave, Plato set out a scenario in which a human was imprisoned, staring at a blank wall. Behind the prisoner is a fire that reflects shadows on the wall. In front of the fire and behind the imprisoned, puppeteers perform, casting their shadows on the wall. The prisoner cannot turn around and only ever sees the shadows. To that one person, those shadows are the reality because that’s all they have experienced.

In his allegory, Plato was discussing what constitutes reality — what’s real and what’s perceived. It’s an old subject, but one that always manages to find hold in the public consciousness. While Plato wrote of puppeteers, we’re here to talk about the metaverse and virtual reality. Those concepts were a bit after Plato’s time, so a more up to date example is the Social Technical Imaginary.

“I’d like to introduce this idea that academics call Social Technical Imaginary,” says Rizwan Virk, founder of Play Labs @ MIT. “This is a collectively held vision that often comes from science fiction, but it gets adopted by a larger number of people. Those people have the ability to turn the imaginary into reality.”

Virk, who came to his calling via mobile gaming, is the author of two books on the subject of whether we are living in a simulation and the creator of the roadmap to the simulation point. He is currently with Play Labs @ MIT, a startup incubator in the gaming space.

“How close are we getting to creating fully immersive virtual reality that would be indistinguishable from the physical world,” asks Virk. “To the point where we could consistently fool ourselves into thinking we’re in the virtual world. That lead me to create a roadmap called the road to the simulation point.”

The first few steps towards the simulation point

The first few steps on the road to the simulation point

According to Virk, we are about halfway down the road to the simulation point. We’ve already created gaming spaces dedicated to interaction with a virtual world and other players. We have spectator sports based in the virtual world and the worlds are becoming more photo-realistic by the year.

“Those are the stages we’ve already past,” says Virk. “The stages we are in today are stage 4, which is virtual reality, and stage 5, which is photo realistic VR and augmented reality. As we see better augmented reality, which will be based on glasses initially, we start to blur the line between the physical and virtual world.”

One of the more interesting technologies of the recent past is 3D printing. 3D printers take different materials and create a physical object from a design file, or they create physical objects from pure data. Virk defines this as stage 6.

“As we move beyond the need for glasses, we will definitely get to the point where that line is being blurred,” comments Virk. “We’re seeing that line blurred already with the introduction of 3D printing. You can print everything from a motorcycle to a guitar. Some companies are using 3D printing for blood vessels. We’re starting to see that biology is a science about information, which is what 3D printing is all about. It’s about creating objects from information.”

The next steps

So, where do we go from here? According to Virk, we have a few more steps to go before we reach a true simulation. The next step on the path comes in the form of brain computer interfaces. During his talk he mentions experiments involving implanting chips into different animals and reading their brain waves.

“We’re already seeing quite a bit of progress in being able to read brain signals and classify those,” says Virk. “We have different techniques like EEG, or EMG, which are the brain signals to the muscles. We’ve seen companies use sweat and eye position. We’re trying to correlate all this data.”

Somewhat connected to stage 7 is stage 8, which is implanting memory and learning. As seen in movies like The Matrix, this stage related directly to being able to upload a memory or certain knowledge via a brain computer interface.

“We’re not at the point where we can implant electrical signals and memories yet,” notes Virk. “There have been experiments in learning where they were able to monitor the EEGs of expert pilots while flying. Then they took student pilots, who were learning, when they beamed those signals in, the results were much better. It may not be that far in the future where we can be like Neo and insert a cartridge that downloads the knowledge of Kung-Fu.”

Almost human

Stage 9, the final stage we are currently dallying in, is dedicated to Artificial Intelligence and Non-player Characters. These automatons are computer controller personalities with which we interact in the virtual world. These can be anything from quest givers in World of Warcraft to sophisticated AI chat bots that exist on the web.

The big component we’re missing in AI at the moment is the lack of humanity. Creating AI that are able to pass the Turing test is one of the barriers we have to overcome to reach the simulation point.

“Today, an extended conversation with any AI or NPC will convince us that it’s not human, but we are much further along than we were in the past,” says Virk, but we are not that far off. “It’s much easier to train in the metaverse, in a virtual environment, than it is in a physical environment. That’s why self-driving car companies are turning to virtual environments to do as much testing as possible. It’s much safer that way, and it may be the best way to train these NPCs over time.”

The end of the road

The final step on the road to the simulation point is one we aren’t currently able to dabble in. In fact, we’re not really sure how to deal with this step, because it will require mapping the entire brain and its connections to the body.

“This idea of being able to download consciousness fully, and live in a virtual environment, is now often referred to as a digital afterlife,” says Virk. “The materialists believe that if we can simply map out every single neuron and connection, called a connectome, of the brain, we will then have everything we need to move that consciousness. It’s a concept that is sometimes referred to as substrate Independence. Where you could have that same intelligence or consciousness that used to run on a biological computer running on a silicon computer.”

However, these final pieces aren’t as far off as some might think. Virk estimates by 2050, or 2099 by the latest, we will be able to reach the simulation point. Why is he so sure? We already have living versions of this technology. Now we need to decode how those work.

“When I laid out this criteria, it occurred to me that we already have this technology to some extent,” says Virk “People always ask me ‘when will we reach the simulation point,’ well my estimate is that we’re still a few decades away from that. No more than a hundred years, but it turns out all this technology already exists in biological form and it happens every night when we dream.”

Don’t tell Jeff, but the first thing I’m going to download is Astro’s Playroom cheats so I can beat his scores. To check out more of this talk and hear all the details and caveats directly from Rizwan Virk, check out the GB Summit: Into the Metaverse 2 event!

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This Top-Rated PDF Solution Is 66% Off Now

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Opinions expressed by Entrepreneur contributors are their own.

Paper has made its way largely out of business, but that doesn’t mean you don’t still work with documents regularly. Instead, we’re just working with them differently: with the dreaded PDF. These static files can be great if you’re positive that a document is ready, but a serious nightmare when you have to make changes. When you’re working with a lot of PDFs, you need a quality digital solution.



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UPDF Pro is one of the top-rated PDF solutions on the market. Geeky Gadget writes, “UPDF is a potent PDF editor and PDF converter designed to stay up with advanced technologies. It ensures that whichever features you use are up to date. UPDF not only converts PDF to Word but can perform many advanced editing.” Fossbytes adds, “UPDF doesn’t have a boring interface like other PDF software. The design is stunning and eye-catching. On top of it, it is convenient to use. You wouldn’t be bothered with a complex design that is very time-consuming.”

These are just the tip of the iceberg of positive reviews for this all-in-one PDF solution for individuals and businesses. With it, you can edit any PDF document across Windows, Mac, iOS, and Android devices, adding or deleting text, editing fonts and color, and much more. The tool allows you to add, crop, rotate, replace, extract or delete images, watermark documents, and password-protect them for elevated confidentiality. You can also easily annotate PDFs, highlight, underline, or strike out text, add shapes and notes, and much more. Finally, it’s even easy to convert any PDF to Word, Excel, PowerPoint, and a ton of other file types in just a click.

Working with PDFs has never been easier than with a lifetime subscription to UPDF Pro. Grab it on sale for 66% off $149 at just $49.99, the best price you’ll find online.

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Using data to boost event ROI

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Events are essential to any marketing strategy. Because they have the power to bring people together, events offer a unique opportunity to engage and deeply connect with a target audience while enriching a sales pipeline for the business. 

During the pandemic, events went through a transformation. In addition to navigating drastic changes to how and where we met, event experience leaders employed new technologies to facilitate connections. In so doing, they learned more about improving event experiences for all attendees, speakers and sponsors. The most significant change to events: Technological advancements enable event organizers to act on data insights before, during and after an event to optimize outcomes.

As we enter a new era of events, it’s more critical than ever to know how to capture the right data — and use it meaningfully. According to a recent survey of more than 200 event organizers, 85% plan to host at least three in-person events in 2023, with 35% planning to host at least 10. The opportunity is ripe to unleash the power of event data to maximize business impact. 

In-person events, reimagined with better data 

With event professionals producing in-person events again, they bring the lessons learned from more than two years of constant upheaval and technological transformation. Event experience leaders at all organizations are tackling the “event impact gap”: The disparity between event organizers’ aspirations to produce impactful experiences and their ability to execute those goals with available technology.

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While the role of event organizer has been evolving for many years, the pandemic quickly accelerated the change. In addition to planning and logistics expertise, event organizers now bring a host of other skills to the table: data analysis, marketing operations and digital production. But even with their enhanced skillsets, organizers continue to wrestle with outdated event software that keeps them from accessing and activating their data. That obstacle hinders organizers’ ability to design and execute personalized experiences and truly connect with their audiences. 

Better data activation empowers marketers to personalize outreach and drive engagement at scale, incorporating events deeper into their demand generation strategies. This fosters attendee engagement, driving increased revenue and ROI. 

Leveraging data to accelerate pipeline

In-person events possess enormous data potential waiting to be unlocked. Events stand out as a prime opportunity to understand how your target audience behaves, where their interests lie and what engages them deeply. When you’re onsite, you have an unparalleled window into the content, peers and exhibitors that appeal to your audience and how the audience is connecting to your brand. These insights inform both your future event strategy and your broader marketing strategy.

Use data to engage attendees

It’s one thing to decide what data to collect and another to be strategic about what you’ll do with the data. Event organizers’ experience executing virtual events showed that having access to data is half the battle. The real value of your data lies in your ability to turn it into something actionable and use it to your advantage. How do you bring the behavioral and engagement data you collect into the extended marketing fold? You need technology that enables your teams to use your data instantly and easily to personalize post-event content and communications. 

With the knowledge of whom an attendee interacted with, the sessions they liked and the type of content they downloaded, you’ll craft more effective outreach. This extends the value of your event for your attendees and your demand generation efforts. Rather than sending the same message to every attendee, with their name appended to the beginning of an email, you can use data to rouse your attendees’ interests and keep them meaningfully engaged. 

Understanding how engagement translates to leads  

The same data you use to customize an attendee’s event experience can enrich and accelerate your sales pipeline. By capturing insights into attendee activity — the polls attendees participated in, the sessions they checked into and the exhibitors they spent time with — you can use robust event experience technology to assign engagement scores to each attendee. From there, you can segment attendees by their levels of engagement and personalize your post-event follow-up.

In addition, equipping sales teams with the data needed to prioritize the most engaged leads lets them focus their time and efforts on maximizing conversion success. And because of the rich data you’ve collected about each attendee, sales teams can discern whether a correlation exists between an attendee’s high engagement levels and their likelihood of becoming an opportunity, enabling better future strategies.

Using data-enabling technology to refine experiences

Data-enhanced experimentation isn’t limited to your sales team. Events of all formats offer ample opportunities to experiment, iterate and improve experiences and business outcomes — before, during and after an event. 

Ensure you collect data corresponding with your event format. For instance, an in-person event with a virtual component requires data collection strategies for both audiences. Customize questions to speak to the distinct experiences of virtual and in-person attendees. And use event software that supports audience engagement measurement both on the floor and through the screen.

Maximize the value of behavioral data 

Use registrants’ behavioral data to build personalized session tracks and networking opportunities. Collecting behavioral data at in-person events can feel daunting compared to virtual events, but it doesn’t have to. Event experience leaders are leveraging new solutions like wearable technology to gain insights.

Today’s wearable event technology has the power to offer attendees more personalized networking and session experiences while simultaneously giving organizers unmatched data capture. Your budget may not permit wristbands, high-tech badges and other wearables as must-haves for every event, but they function as a powerful data source. When attendees wear these devices, they automatically provide information to help you optimize future events. Depending on the technology you employ, you’ll gain: 

  • Advanced analytics, such as dwell time.
  • Records of touchless contact exchanges.
  • Event gamification for attendees.
  • Lead collection for sponsors.
  • Integrated tracking and reminders for session check-ins.

The behavioral data you collect, combined with pre- and post-event surveys, deepens event insights and facilitates more personalized opportunities for attendees, speakers and sponsors. 

Experiment and follow the data 

Data empowers event experience leaders to test new ideas and follow where the data leads. 

Experimentation can apply to anything from registration forms and email marketing subject lines to in-session polling strategies and other event messaging. Start small, and choose three to five key metrics to test based on past event data. Once you put an experiment out into the world, evaluate the results. Then plan for your next experiment based on what you learned and pivot your event strategies as needed to keep refining your efforts. 

Data maturity powers advanced insights 

Actionable data not only enables better event experiences, it also empowers CMOs and marketing leaders to demonstrate the impact of events. Prioritizing a data maturity model ensures you can effectively communicate the value of your event experience program to all stakeholders, especially as organizations navigate economic uncertainty. Rather than evaluating data in a vacuum, a data maturity model connects each event touchpoint, providing insights that allow you to align event strategy against key success metrics.

Four steps comprise data maturity: 

  • Data capture: Accessing your data is the first tactic. Your organization needs the ability to gather data holistically, including granular information like session attendance and demographics. 
  • Data integration: Connecting the data you capture to your business systems enables you to take action in the future. 
  • Data utilization: Use the integrated data to offer the audience more valuable event experiences. Identify and curate precise data points to help achieve personalized experience goals, such as customized communications, to help increase conversion and attendance rates. 
  • Data translation: Take what you’ve learned from past events and act. Using actionable data insights from past events to inform decision-making results in a virtuous cycle, constantly renewing and improving event experiences.  

When you can access, integrate and activate your event data, your teams will maximize ROI by optimizing the attendee experience, driving lead generation and contributing to overall marketing goals in measurable ways.

Attendee expectations continue to evolve, and rather than trying to return to business as usual, event experience leaders must leverage data to direct and inform event decisions. There’s never been a more exciting time to collect onsite and virtual data, experiment and iterate on data findings, personalize event experiences and take your sales pipeline to the next level. 

Alon Alroy is CMO and cofounder of Bizzabo.

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The future of generative AI and its ethical implications 

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Generative AI is revolutionizing how we experience the internet and the world around us. Global AI investment surged from $12.75 million in 2015 to $93.5 billion in 2021, and the market is projected to reach $422.37 billion by 2028.

While this outlook might make it sound as if generative AI is the “silver bullet” for pushing our global society forward, it comes with an important footnote: The ethical implications are not yet well-defined. This is a severe problem that can inhibit continued growth and expansion. 

What generative AI is getting right

Most generative AI use cases provide lower-cost and higher-value solutions. For example, generative adversarial networks (GANs) are particularly well-suited for furthering medical research and speeding up novel drug discovery

It’s also becoming clear that generative AI is the future of text, image and code generation. Tools like GPT-3 and DALLE-2 are already seeing widespread use in AI text and image generation. They have become so good at these tasks that it’s nearly impossible to distinguish human-made content from AI-generated content.

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The million-dollar question: What are the ethical implications of this technology?

Generative AI technology is advancing so rapidly that it’s already outpacing our ability to imagine future risks. We must answer critical ethical questions on a global scale if we hope to stay ahead of the curve and see long-term, sustainable market growth. 

First, it’s important to briefly discuss how foundation models like GPT-3, DALLE-2 and related tools work. They are deep learning tools that essentially try to “outdo” other models by creating more realistic images, text and speech. Then, labs like OpenAI and Midjourney train their AI on massive datasets from billions of users to make better, more sophisticated outputs.

There are numerous exciting, positive applications for these tools. But we would be remiss as a society not to recognize the possibility of exploitation and the legal gray areas this technology exposes.

For example, two significant questions are currently in debate: 

Should a program be able to attribute the results to itself, even though its output is derivative of many inputs?

While there is no universal standard for this, the situation has already come up in legal spheres. The U.S. Patent and Trademark Office and the European Patent Office have rejected patent applications filed by the “DABUS” AI developers (who are behind the Artificial Inventor Project) because the applications cited the AI as the inventor. Both patent offices ruled that non-human inventors are ineligible for legal recognition. However, South Africa and Australia have ruled that AI can be recognized as an inventor on patent applications. Additionally, New York-based artist Kris Kashtanova recently received the first U.S. copyright for creating a graphic novel with AI-generated artwork.

One side of the debate says that generative AI is essentially an instrument to be wielded by a human creator (like using Photoshop to create or modify an image). The other side says the rights should belong to the AI and possibly its developers. It’s understandable that developers who create the most successful AI models would want the rights for content creation. But it’s highly unlikely that this will succeed long-term.

It’s also important to note that these AI models are reactive. That means the models can only “react” or produce outputs according to what they’re given. Once again, that puts control into the hands of humans. Even the models that are left to refine themselves are still ultimately driven by the data that humans give them; therefore, the AI cannot really be an original creator. 

How do we manage the ethics of deepfakes, intellectual property and AI-generated works that mimic specific human creators?

People can easily find themselves the target of AI-generated fake videos, explicit content and propaganda. This raises concerns about privacy and consent. There is also a looming possibility that people will be out of work once AI can create content in their style with or without their permission. 

A final problem arises from the many instances where generative AI models consistently show biases based on the datasets they are trained on. This may complicate the ethical issues even further, because we must consider that the data used as training input is someone else’s intellectual property, someone who may or may not consent to their data being used for that purpose.

Adequate laws have not yet been written to address these issues around AI outputs. Generally speaking, however, if it is ruled that AI is simply a tool, then it follows that the systems cannot be responsible for the work they create. After all, if Photoshop is used to create a fake pornographic image of someone without consent, we blame the creator and not the tool. 

If we take the view that AI is a tool, which seems most logical, then we cannot directly attribute ethics to the model. Instead, we have to look deeper at the claims made about the tool and the people who are using it. This is where the true ethical debate lies. 

For example, if AI can generate a believable thesis project for a student based on a few inputs, is it ethical for the student to pass it off as their own original work? If someone uses a person’s likeness in a database to create a video (malicious or benign), does the person whose likeness has been used have any say over what’s done with that creation?

These questions only scratch the surface of the possible ethical implications that we as a society must work out to continue advancing and refining generative AI. 

Despite the moral debates, generative AI has a bright, limitless future

Right now, the reuse of IT infrastructure is a growing trend fueling the generative AI market. This lowers the barriers to entry and encourages faster, more widespread technology adoption. Because of this trend, we can expect more indie developers to come out with exciting new programs and platforms, particularly when tools like GitHub Copilot and Builder.ai are available.

The field of machine learning is no longer exclusive. That means more industries than ever can gain a competitive advantage by using AI to create better, more optimized workflows, analytics processes and customer or employee support programs. 

In addition to these advancements, Gartner predicts that by 2025, at least 30% of all new drugs and discovered materials will come from generative AI models. 

Finally, there is no question that content like stock images, text and program coding will shift to being largely AI-generated. In this same vein, deceptive content will become harder to distinguish, so we can expect to see the development of new AI models to combat the dissemination of unethical or misleading content. 

Generative AI is still in its early stages. There will be growing pains as the global community decides how to manage the ethical implications of the technology’s capabilities. However, with so much positive potential, there is no doubt that it will continue to revolutionize how we use the internet.

Andrew Gershfeld is partner of Flint Capital.

Grigory Sapunov is CTO of Inten.to.

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