Synthetic media — text, image, audio or video content that has been fully or partially generated by AI — is evolving out of the lab and into commercial products.

In this three-part series I’ll outline how the media production pipeline is being reinvented, driven by the ability of neural networks to imitate the real world.

I’ll be focussing on practical use cases today and in the short term. I’ll leave out the more philosophical questions for now, as I’ve covered that in-depth in the past.

Part II and III coming soon!

Part 1: No cameras, studios or actors required.

Part 2: Programmable Video — Automated Generation at Scale (coming soon)

Part 3: GAN’s & GPT3 — will computers be able to make their own content? (coming soon)

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When we founded Synthesia almost three years ago we had a vision to make it easier to create video content for everyone.

But not just a little easier; our goal was to introduce a paradigm shift in how we think about media production from something we record with cameras to something we program with computers.

Why?

We’re in the early days of a major paradigm shift that will radically change how we communicate.

Imagine the world went back to using pen and paper. We’d all generate 100x less text content than we do today via email, sms and IM.

How will we communicate when it’s as easy to create video as it is to write an email or a tweet?

Humans have always been drawn towards more visual and interactive modes of communication. And we’ve come far since the first text-only newspaper was published in 1665.

I spent my early childhood on internet forums. Back then the internet was mostly text-based, with the occasional GIF, and could barely handle audio streaming, let alone video.

Today, the majority of our online experiences are video driven. We do video calls on Zoom, learn new skills on Udemy, entertain ourselves on YouTube, Twitch or Instagram and the list goes on.

Today’s fastest growing social network, TikTok, is arguably the first major social platform that isn’t just video-first, but more or less video-only — there’s barely any text in the interface.

From research we know that many people respond better to video than they do to text-based information. More senses are activated and our understanding, engagement and retention of the content increases. Conveying ideas and emotions is often easier to do visually than in text.

Yet, only a fraction of the world’s information and ideas are available as video today. Companies are struggling to keep up with the demand for video content. The speed of consumption is massively outpacing the speed and cost of production.

We have made tremendous progress on making it easier to capture video — we literally all walk around with high-definition cameras in our pockets. But our technology for synthesising video via digital processes hasn’t advanced much outside of Hollywood.

Video production is still costly, complex and tied to the physical process of recording.

Our mission is to reduce the entire video production process of cameras, actors and studios to code — enabling humans and algorithms to easily express themselves in video.

Once media production has been abstracted away to an application layer, used via simple markdown language, human creativity will re-wire the online (and offline) experience. Likely in ways we haven’t even thought of yet.

CSS enabled beautiful layouts and graphics. Javascript gave us interactive websites. Smartphones made everything accessible at all times and equipped us with sensors to capture the world around us. ML analyzes and personalizes our digital experiences at scale.

Synthetic, programmable media will be weaved into the fabric of every digital experience in the future — from the personalized news we’ll be watching, to our interactive AI teachers and eventually to the Hollywood blockbuster made by your favourite YouTuber from his or her bedroom.

There’s obviously still a long way to go before we’re making Hollywood films on laptops. Enabling anyone, everywhere to create compelling visual content is an enormous technical challenge. But we’ll get there, and probably faster than we think.

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Just how far are we? Here’s a demo of Synthesia, the world’s first text-to-video platform that works in more than 50 languages.

Simply select one of our built-in avatars (or upload yourself), type in your script, change the graphics and click generate. Your video is ready in minutes.

This new, AI-driven workflow exponentially speeds up the video creation process and decreases costs by a factor of ~1000x compared to camera-based production.

Synthetic video in the next three years

I think of synthetically generated content in three layers of automation, each with their own use cases, scalability and degree of human/machine interaction. Today most tools operate in the first layer; but as companies are releasing public APIs (we just did!) we’ll see use cases proliferate rapidly.

1. Linear Video [accelerating video production as we know it]
   Video content as we know it today, but produced using AI. The price, complexity and time required to make content will drop massively. Making simple video content for training, corporate communications and marketing will become a desk job. Videos are composed by humans using AI tools to synthesize video and audio in any language.
2. Programmable Video [scripted, scalable video production]
   Algorithms enable the production of videos at scale. The templates will be designed by humans, but algorithms will compose videos automatically in the millions each day. Personalized videos, data-driven news bulletins and scalable video chatbots will emerge as videos can be automatically generated via an API.
3. Fully generative video [generative content production]
   As text-generation, like GPT3, and other ‘creative’ AI tools mature and become useful, algorithms will be able to somewhat autonomously create content. People love to speculate on the sci-fi end of the spectrum here — and I’m sure we’ll see some crazy things — but I think the actual business impact will be less exciting. For example, imagine an AI bot that automatically converts written articles into a video by summarizing the text, transforming it to spoken-language and pulls in matching images to create a short video. And does so in 40 languages.

This blog will focus on the first part, exponentially scaling up the production process for the type of video content we are familiar with today.

Why traditional video production will never scale

Video production is an extremely fragmented and multidisciplinary process. It can be divided into roughly four steps: creative (script) + camera capture (recording session) + post production (video editing) + distribution (video hosting).

Even a simple corporate video production can easily be $5000 or more. While the cost is easy to understand the complex workflow around video creation is less understood by non-practitioners.

1 — Cost, time and complexity

Writing scripts, renting a studio, hiring actors, renting cameras/light/sound and post-production makes the video recording process expensive, time consuming and complex. It involves many stakeholders and it’s a weeks, if not months, long process to make even very simple video content.

Even bare bones video, say of an executive giving a monthly update, requires you to get the right people in the room, finalize the scripts, record several takes, upload the footage from the camera, do some post-production, render and then you’ll have your video. It’s a long, drawn out process that requires lots of compute, storage and working hours.

2 — Video is linear and can’t be edited

Once you’ve made a video the traditional way it’s set in stone: if you misspoke or want to add/remove something you’re out of luck. So you need to ensure that you have your script down before you start recording. You can’t creatively experiment or update messaging once it’s been shot, unlike text and images which can be dynamically altered.

3 — Camera anxiety

Most people don’t like being on camera. They want to look good, sound confident and not come off as stiff. Performing even a simple message to the camera can be hard without doing many takes and can take up a lot of mental space for whoever is due to be recorded.

If you do have someone internally who likes to be on camera you need to schedule recordings, creating time lag and additional complexity. And what do you do if that person stops working for the company?

4 — Difficult to translate

If you are a global company creating multilingual content you also have the added complexity of translation and subtitles/dubbing/reshoot. You’re faced with the tradeoff between using a presenter, which is much more engaging, or sticking to text or voiceover which is easier to translate but not as engaging.

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The communication chasm

Companies create much less video than they’d like to. Due to the complexity of production, video is still seen as a project-based activity rather than a continuous process like writing email, documents or working with slide decks.

This creates a communication chasm. In 2020 text-based communication just isn’t the ideal way to communicate with employees or customers.

In the retail sector for example, you are dealing with a high employee turnover, many part-time workers and a workforce who might be less literate than average. In these cases sending a 4 page PDF document over email is not an effective way to communicate.

A client reported that store workers either didn’t read the documents or skimmed them quickly without understanding them. Now, using videos that are shown at the team meeting and sent via email, there’s a much higher degree of information retention amongst the workforce.

It’s deeply interesting to me just how much the medium shapes the message. I predict we’ll see a fundamental shift in how we communicate over the next decade, and while it might seem strange today, I truly believe we will see an explosion of video/audio based communication when it’s as easy to create as writing an email.

Enter synthetic video: digital and programmable

Synthetic video offers an entirely different and fully digital workflow. Reducing the entire production process to a few clicks or an API call exponentially improves the workflow and allows for entirely new opportunities.

In August we released Synthesia CREATE, the world’s first text-to-video platform that works in 39 languages.

Simply select one of our built-in avatars (or upload yourself through a simple recording process), type in your script, change the graphics and click generate.

Your video is ready in minutes and it doesn’t require anyone to move from their computer or to be dependent on any physical processes or other people’s calendar. With pricing that starts at $30 / month synthetic video is a truly accessible tool.

Make your own video for free here!

2020: Linear video production at scale.

This new, AI-driven workflow exponentially speeds up the video creation process and decreases costs by a factor of ~1000x compared to camera-based production.

Some of our clients use the Synthesia platform to create videos end-to-end and others use Synthesia as a ‘virtual camera’ to generate live-action sequences that are then further edited in Adobe Premiere or other traditional editing suites.

For linear video production — the kind of video we are familiar with today — the implications of synthetic video is exponential. Particularly in marketing, corporate communications and training:

• Create synthetic videos on-demand as events happen.
• Multilingual corporations can make videos in 39 different languages.
• Not happy with your script? Simply edit and re-render your video in a few minutes.
• Want to communicate in foreign languages? Click a button and we’ll translate your video.
• Create videos at the speed with which you create slide decks.
• The whole production process can be handled by one person.
• New policy or regulation? Load up your original video, edit the script and re-render the video to reflect changes.
• Make senior executives into AI presenters and alleviate them of having to take time out of the calendar to do tedious video shoots.
• Batch-generate videos via our API.

Turning text into video

While synthetic video can certainly replace some of the content you would otherwise have recorded with a camera, we don’t view synthetic video as a replacement to normal video.

It’s a fundamentally new medium that will expand, rather than replace, the video market. As the price to create a video drops to a few dollars it will allow companies to create much more content than they otherwise would have done.

What would otherwise have been text or slides are now being made into video with very little additional overhead. And this actually where synthetic video shines — not as a replacement for normal video production, but as a replacement to text.

Some of our customers are accelerating their existing video production and are now creating 10x as much content as they did before, with synthetic content sitting alongside their traditional video content.

Others have never produced video before they started using Synthesia and are now publishing entirely synthetic content.

For example we’ve helped a local youth educator in Brazil create a video course for software development and helped another customer train restaurant workers who are currently restricted from doing in-person training due to the pandemic.

Next up: Programmable, personalized video content.

Next part in this series I will cover the power of creating videos through API — from making it easier to create videos to making it entirely hands-off. Once scripts are in control of making videos the scale is unprecedented. With a little bit of programming everything can be turned into a personalized video.

https://www.youtube.com/watch?v=1ogbUbzuYUY

Follow me here on Twitter or our newsletter to get notified when the next part is released.

1 — Synthetic Media will expand from fun, consumer applications and into B2B media production pipelines.

My overarching prediction for 2020 is that we will see Synthetic Media move from being primarily used in fun, consumer applications to making its way into traditional media production pipelines.

Today, the gap between how much media content companies want to produce and what they can afford cost/time wise is very large.

Synthetic Media will bridge that gap; making it easier and more cost-effective to produce large amounts of audio, video or image content without the need for costly, physical processes.

Three years into building Synthesia I am convinced that the impact of these technologies will be similar to that of synthetic instruments (making music on a computer) and PhotoShop (creating images digitally).

In 2020, I predict we will see the three first use cases for synthetic video catch steam. Within the next 3 years I am convinced that AI video editing of some form will be a line item on most video production projects, just like Photoshopping or color grading is today.

Synthetic images will enter the stock-photo market
You’ve probably seen the website that generates fake pictures of humans. If not, check it out here.

In 2020 these GAN-driven technologies will be used commercially to synthesise images of not only humans but also landscapes, objects, homes and so.

Due to the near-zero marginal cost of creating new images we will see companies building marketplaces that host a vast amount of synthetic images that are much cheaper than traditional stock photography (which is already really cheap).

Rosebud.AI are already offering images of humans.

AI-video editing: translation / personalization
2020 will see a significant uptake in the use of AI to edit videos — taking existing video and enhancing it through personalization or seamless translation.

Scale content across geographies is primarily important for advertisements and corporate communications. AI dubbing will take a single video and natively translate it into any language, without degrading the quality of the video. We’re already working with many Fortune 1000 companies to translate and expect to significant scale up operations in the coming year.

We documented the effects on viewer engagement using traditional overdubbing vs. AI dubbing and the results were significant.

Personalization will also be massive — we live in a world of increasingly personalized experiences making it difficult for brands to stand out in the deluge of online content. Personalized video will be an important tool to capture the viewer’s attention and it is the natural step up from personalized emails and images.

AI-generated text-to-video (end of year)
End of year we’ll see the first commercially available products to generate entirely new video (as opposed to enhancing/editing them via translation or personalization) by simply typing in text.

A real actor will be used as the avatar but can be made to say different things by using text-to-speech technology as the input to the system.

One of the first use cases for this technology will likely be virtual assistants and chatbots where synthetic technology can provide a lifelike experience compared to the very CGI-looking products that exist today.

While AI-driven video synthesis has advanced far there are still fundamental problems to solve in body language, audio/voice and scalability before you’ll be able to generate an advertisement purely through software without the need for cameras.

But in the future, video creation will be as easy as writing an email; and this will be the first step to fully automating that process.

2 — Synthetic voice will cross the uncanny valley

Synthetic voice has improved a lot in the last couple of years. Yet we (in my opinion) have yet to see production ready voice synthesis that truly escapes the uncanny valley and are usable as a replacement to traditional actor-driven voice over.

Today voice synthesis technology is primarily used for virtual assistants such as Siri or Alexa.

In 2020 I think we’ll see rapid adaptation of voice technology in traditional media production pipelines. Particularly in video games and audio books which are markets that today face significant challenges scaling human voice over.

Think about gaming — vast amounts of dialogue needs to be recorded in a studio using actors. Voice synthesis is a cost saving mechanism, but it also opens up new possibilities for much more open-ended dialogue from in-game characters. Speech snippets can be rendered out on demand as opposed to being pre-recorded in a studio.

I believe adaptation will be driven by significant technical leaps in two major areas:

The ability to easily generate many different voices
It’s still difficult to create many different sounding voices at scale. Alexa, Siri and similar technologies are the products of lots of effort and resources to produce a single voice — often requiring very large datasets for training.

For personal assistant type of use cases a single voice works well. But as a tool in traditional media production the ability to easily create new, unique voices is important — each brand or company will want their own distinct voice(s) that are in tune with their brand and tone of voice.

Controlling emotion, speed and pronunciation
Would you like to listen to Siri read out an entire eBook? Likely not — for short voice snippets the voice quality is digestable, but it lacks the emotion, pronunciation and variations in speed that makes it interesting to listen to.

Several companies are building creator-tools that enable a human editor to change and modulate the voice to fit the content. In the near term this human-assisted approach will be key to producing high-quality results.

Companies worth watching: Zenith, Deepzen, Modulate.ai, Replica Studios, Respeecher, SpeakAI

3 — Ethical Standards will Emerge

As more and more companies look to synthetic media technologies to accelerate their content creation we will increasingly see these companies take a formal stance on how to use these technologies and which providers to work with.

Tech companies have been under lots of scrutiny in the past couple of years, and as new technologies rapidly develop more and more companies are starting to think deeper about how the products they build impact not just the bottom line but society as a whole.

We’re seeing this up front and center in regards to environmental issues but also in areas such as facial recognition or privacy (eg. Apple limiting use of social media). Synthetic media brings similar questions forward; are we OK doing non-consenual content if clearly marked? Should viewers know if they’re watching a synthetic video? How do we pay actors for their likeness?

We published our own internal framework for ethical use of synthetic media which can be found here.

4 — Consumer applications of Synthetic Media will be on the rise

In the past year we’ve seen many examples of consumer-driven synthetic media technologies evolve.

Snapchat released their gender-swap filter almost a year ago. FaceApp made us look older and spurred a (really) weird conspiracy theory that it was all a ploy from the Russian government to gather images of our faces. ZAO released a ‘deepfake’ app that can swap the users face into pre-selected clips from well-known film and tv (and also spurred a weird conspiracy theory).

FaceTunes parent company, Lighttricks, raised $135m to build what I think of as the content creation suite for Gen Z — accessible photo/video editing apps that are born on mobile and are able to produce professionally looking results without the effort or skills traditionally required. In the not so distant future I am convinced that this will be the de-facto way to create fast content for brands. Canva is a great indicator of the easy-to-use content creation tools that we’re headed towards.

I predict we’ll see more and more of these kinds of applications and that we will increasingly see apps and/or social networks revolve around a particular synthetic media technology. For example Instagram (in part) took off because of the ability to use filters that made any photo look great.

It’s not hard to imagine the next iteration of Tiktok being one where users can sing beautifully, cos-play as their favourite celebrities or create their own digital avatar to express themselves.

5 — Deepfakes won’t impact the 2020 Election

Will we see Dr. Fakenstein-style faceswapping and other satirical videos/PSA’s emerge? Definitely. But I highly doubt we will see any genuine attempts to use deepfakes for disinformation purposes.

Why?

Reading the news makes it look like it’s easy to create synthetic videos. In reality it’s really, really hard — particularly if the goal is to edit what someone says in a video as opposed to merely face swapping which only changes the appearance of the face in a video.

Secondly, the speed and scale at which such a video would get debunked (see Nancy Pelosi which wasn’t even a deepfake) compared to the production costs would simply not be worth it today.

Politicians and public figures have significant means of providing provenance of video. And unlike text-based disinformation, which can be more nuanced in the way the lie is presented, a video is demonstrably either real or not.

For now it’s simply much easier, effective and more scaleable to write fake articles or do basic image/video editing to change the context of existing media. That is also what most experts will agree on — even basic image/video editing is only prominent in around 10% of all disinformation today. The rest is purely written disinformation.

That said, I’m sure the media will go bonkers either way.

As synthetic media technologies evolve and increasingly become an integral part of the media production value chain it is important that we as technology providers take responsibility for the ways in which our products are used.

We propose a simple framework of consent, control and collaboration for working with synthetic media in a commercial context and it is our hope that other companies will join us in following these simple guidelines.

Synthesia technology is already used in video production today to translate and personalize video content in a much more scaleable way than what has been possible before. If you’re curious to learn more about how our technology is used today have a look at our website.

Synthetic media will significantly accelerate creative expression and lessen the gap between idea and content, for good and for bad. It will bring with it new methods of communication and storytelling, enable unprecedented human-computer interfaces and challenge our perception of where the digital realm begins and ends.

The capabilities to edit and synthesise media is of course nothing new. Visual effects in the film industry has been around since film was invented. PhotoShop was released in 1991 and evolved photography from an analog to a digital creation process. Software synthesisers enabled a generation of bedroom producers to create chart-topping hits from their laptop.

More recently Snapchat, Facebook and Instagram has pioneered face filters and similar editing tools that have given everyone the ability to express themselves through beautiful and creative images.

These technologies have changed the equation of entire industries in their own right. AI-driven synthetic media technologies will be the next big paradigm shift.

These new technologies also bring with them challenges around truth, identity and media provenance. How do we protect our voice and visual likeness from being abused by people with malicious intent in the era of synthetic media? We have already seen the issues that arise when everyone can broadcast anything through social media platforms that often amplify emotional and provocative content rather than the truth.

It is clear to us that artificial intelligence and similarly powerful technologies cannot be built with ethics as an afterthought. It needs to be front and centre, an integral part of the company.

We expect these rules to mould over time as synthetic media technologies evolve and become part of our daily lives. If you have ideas or comments please feel free to send us an email.

Consent

• No-one should be synthesised without consent. We propose implementing a digital consent system to streamline the process.
• For example, synthesising public figures without consent violates these ethical guidelines no matter the intention of the content.

Control

• Actors should be in control of their likeness and should have access to a record of all synthetic media content they appear in.

Collaboration

• A general willingness, within reasonable means, to engage in public discourse and education around synthetic media.

The Future is Synthetic

Update: 4th September 2020

Reflecting back on this piece a year later it feels more clear than ever that we’re moving towards synthetic media future. Since I wrote this article the technologies have matured, we’ve seen a surge in startups and most importantly synthetic media is being used everyday by both independent creators and Fortune 500 companies.

10 things that happened since I wrote this article in summer 2019:

• We launched the worlds first text-to-video platform and have created more than 15,000 videos in out first months of launching.
• Samsung NEXT released their synthetic media landscape covering more than 50 startups. We did the video for it.
• Reface.ai became the #1 downloaded app on the US app store.
• WIRED ran a feature on how we created personalized video learning courses for 100,000 employees at WPP. We also worked with Snoop Dogg.
• Deeptrace changed their name to Sensity and released their Visual Threat Intelligence platform.
• Adobe kicked off their Content Authenticity Initiative which looks very promising.
• Lyrebird merged with Descript and released Overdub to bring synthetic podcast editing to market.
• Rosebud released a photo-editing platform for switching out the face of models in images.
• Microsoft released a free-to-use detection tool for deepfakes. Google and Facebook seems to be working on it.
• Lastly, it feels like the mainstream discourse is (slowly) changing to discern between good and bad synthetic media. As tangible products emerge (vs. cool/’scary’ research projects) it is, not surprisingly, a lot easier for people to connect the dots beyond the deepfake headlines.

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In recent years ‘synthetic media’ has emerged as a catch-all term used to describe video, image, text and voice that has been fully or partially generated by computers. The ability for AI-driven systems to generate audiovisual content is, in our minds, one of the most exciting developments enabled by recent progress in deep learning. We are about to see a major paradigm shift in media creation and consumption that will likely change the equation for entire industries.

Synthetic media will significantly accelerate creative expression and lessen the gap between idea and content. It will bring with it new methods of communication and storytelling, enable unprecedented human-computer interfaces and challenge our perception of where the digital realm begins and ends.

We founded Synthesia in 2017 to take the lead in bringing these new technologies to the world. You might have seen our recent work with David Beckham speaking 9 different languages, exemplifying how AI will empower humans to communicate in new, better ways.

But synthetic media also brings with it questions around how we consume and contextualise media. The societal impact of this new category of technologies has been a hot topic in the press over the last two years. The ability to generate Hollywood-grade, or better, visual effects without the budget, time or skill traditionally required opens up the potential for both good and bad.

Our mission is to build synthetic media technologies that maximise human creativity and minimise harmful use of AI. This post outlines our vision for the future of synthetic media and has been born from conversations with researchers, entertainment producers, news organisations, government, celebrities, big tech, advertisers, politicians, NGOs and beyond over the last three years.

From the beginning of time the way in which we create and share our stories has been in constant flux: we’ve gone from cave paintings and printing press to internet, cameras, PhotoShop and Snapchat filters.

All these technologies for creative expression and communication has had a significant impact on society and human relations. Mostly for good, but also for bad. Creative expression is a powerful tool to spread and communicate important ideas and causes but it is an equally powerful tool to spread misinformation and polarisation. This has been true throughout history for each iteration of media technologies; criminals enjoy the benefits of telephones and the internet as much as any law abiding office worker.

There are two sides to creative expression: creation and distribution. They are both equally important. An amazing film has no impact on the world if it isn’t seen by anyone.

Over the last two decades the internet and New Media has democratised content distribution. Blogs and social media has made us all 24/7 broadcasters for free. In today’s world the challenge is no longer to be published, but to be discovered in the deluge of content available online.

Content creation has also advanced, but arguably at a slightly slower pace. Camera phones made us all professional photographers. Music synthesisers enabled a whole generation of bedroom producers to create chart-topping hits on a laptop. Unity and Unreal enabled indie game developers to compete with the behemoths. Snapchat filters gave us mass-scale visual effects for fun and Bitmojis to represent ourselves in the digital realm.

Consider Photoshop. It changed the equation of the entire media industry by introducing a much more scalable, digital and non-linear creation process for producing an image. We can remix images together, add/remove objects, change the appearance of people and experiment with the visual look and feel through a slider-based interface.

Because the creation process has been democratised the internet is now abundant with high-quality imagery and photography from all corners of the world. Just look at Tumblr or Instagram. The marginal cost of producing images is approaching zero which fuels creativity and brings forth talent from all over the world.

Visual Storytelling

Professional video production has not seen the same advancements. Generally speaking we still produce film, tv and advertising the same way we did 15 years ago: actors, cameras, visual effects, post-production. The difference between what a Hollywood studio and a YouTube creator can do is still enormous.

Why is that? Unlike other forms of media such as image or sound we can’t easily edit or synthesise new video without extremely expensive visual effects.

Video is still a linear medium bound to an inherently analog and physical creation process. These limitations mean that video is still primarily used for mass-communication: personalising, translating and making interactive video content is still prohibitively expensive. And the results, particularly translation, often severely impacts the creative quality of the content in a negative way.

But we are right now at the beginning of a major paradigm shift in content creation. Advances in deep learning are enabling magic: neural networks can increasingly reproduce media content at such a high fidelity that it is almost impossible to tell apart from content created by humans. This goes for text, image, voice and video.

It also turns out that neural networks are really good at one of the traditionally most difficult tasks in digital content creation: reproducing human likeness. Creating believable digital humans, both visually and in voice, is extremely hard to do as we’re hardwired to spot even the slightest errors. This is what is usually referred to as the uncanny valley and is why most digital characters in Hollywood films still feels ‘weird’.

Advances in AI are now making the process of creating human voice and video not just much faster but also at a much higher fidelity.

These technologies will enable people to bring their ideas to life in a whole new way. Companies will be able to produce 10x the assets they do today at a tenth of the cost. Mass communication will increasingly become a thing of the past and Hollywood will face global competition as the price for visual storytelling plummets.

Digital assistants will actually look and sound real, virtual celebrities will live on forever and games will feel much more lifelike than they do today.

Our thesis is that over the next decade synthetic media will bring with it fundamental shifts in three areas: content creation, IP ownership and security & verification.

We are excited to take part in shaping this new, synthetic future.

1 — Content Creation & Communication

The cost and skill barriers to creating visual content will evaporate. This will change how we communicate with each other; both on a personal level and in a media context.

As humans we are always striving to communicate through more and more high-contextual media that is closer to a real encounter. The popularity of Instagram, Snapchat, FaceTime and similar platforms are a good indication of how we’re progressing towards visual communication as the default.

Synthetic media will take grainy smartphone video to truly professional quality and beyond. The language barrier will disappear. High-quality visual effects, photoreal avatars, chatbots and interactive videos will be the new default. Meme creators on Instagram will be able to create the kind of content you would see on TV today. Slowly we will use cameras less and move to a more digital creation process, like photos today.

In 10 years the Marvel films of today will be created by film students. Just as with other creative disciplines this will allow people from all over the world to bring their ideas to life without the traditional gatekeepers and intermediates in Hollywood. Good stories will emerge from everywhere; but because the tools are now freely available the creative execution and storytelling will be more important than ever. Visual effects will no longer save a mediocre movie.

We believe the next generation of tools will be much more focussed on art direction as opposed to detailed artistry and pixel manipulation. At Synthesia we are excited to build video synthesis tools that accelerate this creative expression and ultimately democratises content creation.

2 — IP Ownership

When anyone can synthesize anything, what does that mean for IP ownership? Traditionally actors are paid for their time and physical presence. But in the not so distant future you might be able to pay a small fee to have your kids favorite celebrity teach them programming or have Morgan Freeman read out your next audiobook.

That might sound strange, but if you look at how celebrities monetize their likeness today it is not that far fetched: Kim Kardashian reportedly made $40m on her video game (which was a skin to another game) and many celebrities today have their own brand of digital products.

Synthetic media will allow celebrities to scale up their content creation and produce personalised and unique content for their fans. We are already working with celebrities to help them reach a larger, global audience by translating their video content into other languages seamlessly.

It will also be possible, more so than today, to create virtual beings that don’t exist. Lil Miquela, the world’s most popular virtual influencer, today has a team of visual effects artists that manually create the content. Soon the ability to create these avatars will be democratised and we’ll see a surge in this new type of IP and storytelling. Disassociating fictional characters from real actors will be an interesting shift.

Is it Harry Potter or Daniel Radcliffe that people all around the world love? And what would it mean if there was no Daniel Radcliffe, only a virtual Harry Potter?

As we move into this new world of synthetic media it is important that everyone has control over their likeness and can control when and where they are being synthesized.

A core part of the Synthesia mission is to ensure a digital consent / record is in place, not just for actors, but for all of us. Being in control of your real-world individual likeness (and in the future all IP of the characters you create) will be important to enforce through technology.

3 — Security / Verification

Synthetic media technologies also bring with them challenges around truth, identity and media provenance. How do we protect our voice and visual likeness from being abused by people with malicious intent if anyone can create anything? We have already seen the issues that arise when everyone can broadcast anything through social media platforms that often amplify emotional and provocative content rather than the truth.

As a society we will both have to educate the public and build technologies that can contextualise the media we consume. Synthesia are also working to push forward industry standards and implement ethics as a core part of the company.

Soon we will need to be as critical towards videos as we are towards photos today and not assume that what we see is necessarily real. This education will take time. We believe the best method to educate is exposure: once people start watching celebrities speak foreign languages, interacting with virtual avatars and create their own synthetic media they will increasingly become aware of these technologies.

But we also need to develop tools that can automatically contextualise and verify the provenance of the media we consume. This has to be a collaborative effort between many different parties. Solutions that work in isolation will not be good enough.

Technically we think it’s important to separate between the two main areas of security: detection of fake videos and verification of authentic content.

Detection is a simple idea: train AI systems to recognise synthetic media eg. DeepFakes. Synthesia co-founder Matthias Niessner recently published FaceForensics++ a state-of-the-art system for deepfake detection, developed in his lab at TUM. We believe this potentially will be a good short term solution, but it will be an arms race.

More importantly, we believe that in 5 years almost all content will be synthetic, just like almost every image today has been through PhotoShop. By far the majority of that content will be positive, like it is today.

We think the much more important question for society in 3 years will be if the content is consensual or not. This could happen through a protocol that allows content producers to fingerprint their content and for consumers to verify authenticity automatically. Ideally this would be some sort of open protocol that would be adopted widely on the internet like SSL has been for financial transactions. It is by no means a perfect solution but it would be a significant step forward in terms of verifying video, particularly from official sources.

The technical challenges of building verification tools are still in the R&D domain. Historically the issue with watermarking and fingerprinting content is that it only works within a defined ecosystem and that it breaks down as videos are compressed, trimmed and embedded into other videos (eg. a YouTube blogger editing in a video from the BBC).

In order to solve these problems we believe that the starting point is the ability to synthesise videos in very high quality. We’re actively working on technology that utilises AI to recognise and fingerprint video in way that works ‘in the wild’. In future blogposts I will expand on our thinking and work in this area.

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At Synthesia we are excited about this new future we are moving into and we’re aware of responsibility we have as a company. It is clear to us that artificial intelligence and similarly powerful technologies cannot be built with ethics as an afterthought. It needs to be front and centre, an integral part of the company: reflected in both company policy and in the technology we are building.

In future blogposts I will expand on our thinking in these three areas. To follow our progress visit our website.

We at Duuoo believe that the era of HR is over. Why? Because humans are not resources — they are humans.

Years ago a similar shift took place.

Businesses started taking the customers point of view. They focused on delivering the best experience possible. On giving. A fundamental shift from viewing the customers as someone from which the company has to extract as much value as possible. The roles has been reversed, and for good reason.

CX, or customer experience, is defined as the sum of all touch points the customer has with a company. Rational, emotional, sensory. From the first story they hear about the product, to buying it, interacting with support and their experience on a daily basis is all part of that experience.

A good customer experience delivers a great ROI. Nurturing and developing current customers is cheaper than acquiring new users. They’ll return, tell their friends and spend more. CRM tools to optimize customer relationships has taken off and today most successful companies use it in one form or another.

A lot of companies today claim that their employees are #1 on their list of priorities, then customers and lastly revenue which will come as a result of the other two points. So why are most companies not actively managing that experience the same way that they actively manage their customer relationships?

We believe that just as you need to manage your customer relationships you need to manage your employee’s experience working in your organization. A new field is emerging — we call it EXM — focused on optimizing the employee experience to attract, retain and develop talent.

The Employee Experience (EX) is the product of the interactions between an employee and the organization/manager over the duration of their relationship. These interactions include an employee’s productivity, happiness, personal development, education and company advocacy. It is measured by the individual’s experience at all points of contact against the individual’s expectations.

A key rule of EX is that every interaction shapes the next. The employee experience is a whole, not just the individual parts. Consistency and adherence to company values is crucial.

EX is not just HR with a fancy word. Traditional HR is part of the employee experience — transactional touch points such as benefits, salary and vacation policy has a great impact on the EX. But HR has a problem — it only covers a small part of what we call the employee experience. The rest is, in most companies, not taken ownership of.

We think a new generation of tools will emerge, covering much broader than traditional HR.

Compliance and benefits is important. But creating a good employee experience is much more than that. It’s everything the employee experiences from their first day at the company to the last. From office decor and choice of snacks to co-worker relationships and company values.

Transactional and emotional experiences

The employee experience is made up of two types of experiences: transactional and emotional.

The transactional experiences is the practical stuff: do you get paid on time, have easy access to your contracts, benefits, gym membership and so on? All these things are important because they remove barriers for the employee to be as productive and developmental as possible.

Transactional ‘perks’ mainly serve to remove obstacles so that the employee is in the best possible position to develop himself intellectually and emotionally.

The emotional experiences is rooted in feelings: how does the employee feel at work? Does he feel that he is developing himself, that his boss cares about him and that he is getting the recognition he feels he deserves? Does she align with company values, brand, culture and so on?

Feelings are often difficult to quantify and understand properly, which has meant a general reluctance to focus on it. We think that a software-driven movement will arise, helping managers and businesses improving the emotional experiences. And not just by surveying everyone all the time.

Companies like AirBnB, Facebook and their peers invest heavily in creating a people-first workplace. They do so because the return of investment is huge.

happy employee -> happy customer -> profit

They have realized that in the end, it’s a war on talent. And the competition for talent has gone global. The companies with the best employee experiences will end up on top.

3 things we believe will happen:

• We foresee that a suite of software tools to augment managers become better will emerge combining a ‘people-are-numbers’ approach with a more real, human connection.
• The HR department will move towards being responsible for the employee experience. Spend on HR/EX-software will massively increase in the next 5 years.
• The ROI of EX will become common knowledge with time and seen as an investment rather than unnecessary spending.

If you would like to be part of the change joins us at http://exhub.co –we are dedicated to bringing together HR professionals who want to build a great employee experience.

A comprehensive roadmap to save you frustration, tears and cool cash.

This is a long read: it’s two and a half year of learnings from being part of starting more than 11 companies with my great colleagues at Founders.

I’ve distilled all this into 7 principles, a 16 minute read, on how to grow a startup — written from the perspective of someone with a background in traditional agencies.

Why should you read it?

If you’re considering to go into startups (or already have) with an agency background you do not want to miss this. It will save you from learning a lot of painful lessons on your own. This guide is written from your perspective.

If you run your own startup you should read this and pass it along to your marketing department. Make sure that this is not webdings to them. If it is you either have a problem or very deep pockets.

If you work in an agency then this piece will hopefully provide some inspiration on how to move fast, break things and think outside the box.

If you’re already working with startup marketing/growth you will probably have discovered some of this on your own. If not, it will hopefully give you some new perspective and save you some tears and frustration in the future.

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Startups are the cool kid in town. People from all industries are increasingly moving into tech rather than hamster-wheeling their way up the ranks of a Fortune 500 company. Agencies and startups are relatable in many ways and I’ve met a lot of ex-agency people now doing startups.

One thing that I always notice is their frustration that traditional agency tactics does not work in their startup. Especially at the early stages when the uncertainty is high and budgets are low.

Before startups, I worked in agencies and as an independent marketing consultant. I took the journey from executing traditional digital marketing strategies for brands, retailers, etc. to being faced with the daunting, and very different, task of acquiring the first 100 users for a startup.

On the surface, being the ‘digital marketing guy’ in a start-up and in an agency seems like quite similar roles: it’s still about SEM, SEO, social ads, PR, conversion rate optimization and so on.

To some extent the toolbox is the same — it’s how you apply the tools that makes all the difference. And from my experience, the difference in application and mindset is huge; way bigger than people generally imagine.

Based on my own experience of going from a digital agency to a start-up, these are the 7 principles I would have taught myself, if I were to start all over.

Feel free to shoot me questions on twitter @vriparbelli

Let’s dive right in!

Also, thanks to @alencvisic, @jmarovt, @elvismalkovic, @rachelclma and @rayjaw who also did the switch and provided feedback and additional input.

The 7 Principles of Startup marketing

1. You are now on the product team. If people are signing up to your product but not using it, you have a problem. As a growth hacker, you need to be on top of the product analytics and you need to work on the whole funnel, not just awareness and acquisition.
2. It’s a mental battle. There will be times you will be doubt yourself, the product and the team. Let it get to you and set root and you will lose. Instead, accept that there is a huge amount of uncertainty in a start-up. Reduce the doubt by talking to customers and listen to their feedback to give your ideas some direction. Keep an eye on the data and keep testing — always testing until you get it right.
3. Avoid premature optimization. Don’t spend too much time optimizing Facebook campaigns trying to achieve that 5% reduction in CAC. The opportunity cost is not worth it at the early stage. Focus instead on trying new things that might make an even bigger difference.
4. Don’t look where others are looking. Marketing channels come and go. The big ones become more and more saturated over time. You can’t compete there. Instead, find, hijack or create new channels. Think different and always be ahead of the curve! This might seem difficult to do at first, but if you are able to think about ideas that cross channels and have a clever developer to bounce ideas off, you’ll be surprised what you can come up with.
5. Execute, execute, execute. In a startup, you need to be a Swiss army knife, everything has to be done with your likely small team. If you can’t do the ad creative yourself, your designer will have to it. This takes away their focus and could slow down the whole team. This doesn’t mean you need to be a hard core creative or a serious coder, but you should be open to learning new skills, at least to a point where you can test whether any idea or concept you have will actually work (i.e. you should be able to create the minimal viable product). Go with the 80/20 principle.
6. Avoid perfectionism and be BOLD. Your focus should be on testing, not on being pixel perfect. And don’t be afraid to polarize. In fact, you should aim to shake up things and divide people. More often than not at bootstrapped startups, it’s the radical/bold changes that can generate the big swings you’re looking for.
7. You’re the expert. Most likely, there is no one who will tell you what to do. You are expected to be the expert in the field. And if you’re not, become one!

Welcome to the product team

In an agency, your job is to sell someone else’s product. If the product is no good, your job will be more difficult, but it’s out of your hands. In an start-up, however, the boundaries between marketing and the product development are blurred — particularly for SaaS products.

If your start-up’s product is bad, you have a serious problem. Growth also entails a good deal of product development. It’s your job to make sure that people come back and spend more money and tell their friends.

The figure below explains the difference between doing marketing and growth. In marketing, you work mostly in the top of the funnel doing awareness and acquisition campaigns, while as a growth manager, you need to look further down the funnel.

Bringing people to your website doesn’t matter in the long term if they don’t sign up. Getting users to sign up is a wasted effort if none of them come back. You need to be on top of why your users are churning and take measures to limit this churn and keep users. This also means looking deep into the product as well.

In an agency terms: you will likely be responsible for the desk research, focus groups, customer surveys, product management and channel execution.

That’s a high workload to keep on top of. This is where as a startup marketer you’ll be working a lot leaner than what you’re used to at an agency. For instance, to make a marketing decision in your start-up, you won’t need to invest in incredibly thorough, full insight projects to justify decisions. But on the flip side, in a startup, you might find you are asking yourself the following question, a lot …

It’s a mental battle

Are we selling it wrong or selling the wrong product?

It will drive you crazy. Unfortunately, in the early stages you will most likely remain in this flux for a long time. Unfortunately, the amount of uncertainty in an early-stage start-up can be overwhelming. It’s therefore important to keep a steady sense of direction, even in moments when you are seriously doubting yourself and the company.

On a personal level, a failed agency campaign probably just means an angry boss and dissatisfied customer. However, a failed start-up is a whole different ball game and would mean you losing your job along with going through a great deal of emotional stress. If you let this fear paralyze you, you will lose.

So how do you take action on this and answer your doubts? The key is to keep talking to your customers — they will tell you if they are happy or not with the product. To talk to your customers you could implement Qualaroo surveys, call them up, send them emails or utilize a host of other means, just figure it out. In the words of one entrepreneur:

“If you’re selling the wrong product — the rest doesn’t matter. So until you can confidently say that your product absolutely delights a certain target group — focus on this issue 100% of your time.

Talk and meet with your 5–10 early customers (hopefully you have them — otherwise check here) and figure out a way to iterate on the product until it’s absolutely indispensable for your target group. Then all the next steps are going to be much easier.” Jakob Marovt, Co-Founder of Pipetop.

• Make it a priority to get quantifiable and qualitative insights from your customers.
• Work closely with the product manager. If there is no product manager, make sure you are the voice of your customers when talking with designers and developers!
• Be aware of focusing too much on awareness and acquisition. If 80% of your sign-ups churn quickly, you need to fix that first before pouring additional customers into the funnel.

Rayan Jawad (@RayJaw), Founder of Growth Studio — a marketing optimization and growth hacking agency — has this great, actionable advice for achieving product/market fit:

“Roll the ‘net promoter score’ into your overall strategy and on every major product change, ask your customers this:

“On a scale of 1 to 10, how likely are you to recommend the product to family andfriends?”

Always, always always follow this up with two more questions, which most marketers forget:

1. Why (did you rate this the way you did)?

2. If this product disappeared tomorrow, how disappointed would you be?

Here’s the full details of what to do next. But the gist of it is, if you get a net promoter score of below 8, your focus as a start-up marketer should be to work on the product. If you get a score of more than 8, you’re ready to go full steam ahead with your growth plan.”

Avoid premature optimization

Stop optimizing and start testing

In an agency, you will usually be working with the tried-and-tested channels, such as display, social ads, SEO/SEM, affiliate marketing, etc. In fact, you will usually spend most of your time optimizing:

• A/B testing creatives;
• Extracting data from GA/other tracking software;
• Trying out new keywords;
• Reaching out to new audiences and cultivating those you already have;
• Setting up dayparting, bidding strategies, etc.;
• Managing ad buying on different exchanges;
• ….

In a large ad company, this makes sense. You likely already know what works and, if the company is spending $1m on online PPC campaigns, reducing the conversion cost by 5% is a great win.

This is the reason that large companies focus 80% on executing and 20% on testing new things. However, for a start-up, this should be reversed: 80% of your time should be spent trying out new things and 20% on executing those that (sort of) work.

In time, this ratio should skew more towards optimization/execution as you start building a growth model that can yield positive results and that is scalable.

Let’s say you have 20 hours allocated that you can spend either …

1) optimizing your PPC campaigns for a 5% decrease in customer acquisition costs; or

2) testing four new channels by spending 5 hours on each.

Which one should you pick?

Your base CAC will, almost guaranteed, be a lot higher as a start-up with an unknown product under an unknown brand.

The yield, in absolute numbers, should give you a hint on where you should prioritize.

You should be able to get three new customers (the yield of optimising on the startup budget) easier by picking up the phone. Testing new channels will provide you with much more insight and hopefully guide you towards the big win, driving you towards a scalable growth model that you could then start optimizing for real growth.

I’m not telling you to neglect optimizing, of course — but have the above in mind before you start spending days on negative keywords, dayparting and other micro-optimization activities.

“It’s always painful to sit in a board meeting and listen to a company miss the forest for the trees — i.e. even if they make all these incremental improvements that the entire company is focused on, they’re going to end up at 2X, and they need to get to 100X.” Sam Altman, Y Combinator source

• Don’t get hung up or lost in the details. You need to move fast!
• If you have something that works, by all means optimize it. But do the cost/benefit first!

Don’t look where others are looking.

So what do I test?

The freedom to experiment in a startup is obviously different to working in an agency. In an agency, you’re probably not going to suddenly create WhatsApp groups for your customers or to scrape all your competitors’ data to flip it against them in a PR stunt. However, in a startup, experimenting is key. Therefore, it is essential to:

• Keep on top of the newest digital channels;
• Find the backdoors… Don’t be afraid to violate/bend ToS of the big players!
• Focus on generating insights that will help you improve acquisition activities;
• Not limit yourself to online (also do things that don’t scale).

Be first on new channels. The first banner ads on the internet were incredibly effective: they saw CTRs of 80%. Today, we’re down to 0.06% on average. In a start-up, you don’t want to be spending too much time on these highly competitive channels. Be ahead of the curve.

This graph by James Currier explains the issue very well:

You are probably aware of the constantly re-hashed growth tactics that more or less built the below companies:

• The Dropbox referral system;
• AirBnB scraped Craigslist;
• TupperWare introduced the ‘real-life’ affiliate model;
• Tinder focused their efforts on fraternity boys and sorority girls from the same university;
• Harrys made a super-viral video;
• ….

Don’t try to replicate these, unless, of course, they are spot on for you business. These case studies are great for sparking imagination but what works for them will most likely not work for you. Keep in mind that most of these tactics have a limited lifespan. For instance, Hotmail’s ‘PS. I love you’ footer hack worked for them but now it’s been done, it’s unlikely to work again with another company.

These worked well because the methods were new at the time and the product/channel fit were spot on. Nowadays, everyone has a referral system, even ‘single-player’ products with no social interactivity embedded. So don’t get blindsided. Few people still share on Facebook and refer their friends to services — and when they do it’s often for a very good reason.

The most important thing is to have a process!

In Founders, we quickly saw ourselves getting into the mindset of testing, but lacking the tactics to succeed. The nature of early stage growth is chaotic and to not get lost in the wilderness, we needed a process that would help us prioritize correctly.

Therefore, we built the Growth Machine Framework (free download) to implement in our companies. I suggest you either use our template or create your own.

For a detailed breakdown of the growth machine, read here.

When things are working, double down — but keep testing and optimizing. Until you find that one channel that works 50x better than your other activities.

Execute, execute, execute.

Be the Swiss Army Knife

You need to be able to execute by yourself. Bringing a great sense of business or marketing is good, but you don’t want to be the ‘manager’ sitting in the middle of the room who is not able to do anything by himself. In the start-up world, you simply cannot afford to not get your hands dirty — even from a commercial point of view. Get hands on, and stay hands on!

The developers and designers are busy building the product, and if you keep on asking them for help with small tasks, you will quickly become a burden and slow down their work and the whole development team. You should be focused on at least creating an MVP that can prove or disprove whether it’s worth involving the wider business in developing a more scalable solution.

In an agency setting, you usually have design/dev resources available at your disposal — and it’s often the customer that ends up paying for the hours you use to finish a project anyway.

A good start-up marketer has to be a Swiss army knife: good at a lot of different things, expert in a few. In reality, that is probably a bad metaphor because a Swiss army knife isn’t really great at anything — but you get the point, right? It gets the job done — and that’s all you need to do.

Launching campaigns, building landing pages, PhotoShopping ad creatives and pushing it out should not scare you off. Practical skills are key. Hopefully you should be decently prepared if you are coming from an agency background.

Brian Balfour argues that you should aim to become a T-shape, illustrated by the model below. I agree. Learn as many of these as possible.

The good news is that there are a billion tools out there to make things easier. Producthunt.com should be an ‘always-on’ tab on your browser to find ways of making this process easier

Also, outsource if you have to. Or just learn the basics — you will be surprised how far you can get by spending a few days in PhotoShop. Start off copying others’ stuff. It will focus your learning on execution rather than on the aesthetic artistry. Run it through your designers and have them critique your work. Remember:

• The 80/20 principle really applies here. Pick up the basics and get help with the rest if you must.
• Most importantly — become an expert in learning. Read some stuff by Tim Ferriss.

My colleague Simon Sylvest covered this topic in length: If I can’t build a product, what good am I?

Avoid perfectionism and be BOLD

You have no brand. And nobody cares about you.

Be bold and push content that is not perfect. Again, remember the 80/20 rule. This is arguably the biggest change from a traditional agency environment. Start-ups get the Law of Diminishing Returns — the fact that you probably only need less than half the insight a traditional agency would strive for to actually be able to generate commercial value from it. Get comfortable with this.

I asked Rachel Ma (@rachelclma), who also made the switch from agency to startup, what she perceived as the biggest difference:

“Experiencing what it means to “fail fast”, which is something that doesn’t really exist in the agency world. I struggled with this idea during my transition because I took it as personal failure instead of understanding it as part of a process.” — Rachel Ma.

In a start-up speed is key: the speed in gaining some insight, creating an MVP to test, implementing it and rolling out the winners. You need to do a lot in a short amount of time. There is no time for perfectionism. There is a mantra in the startup world that you should “move quick and break things”.

It’s a good mantra, so follow it and avoid agency-overthinking. It does not matter that your landing page design is not perfect or that the copy is not 100% as you want it. You need to fail fast.

Embrace the testing mindset: throw it against the wall and, if it sticks, start perfecting it. It’s a shame to spend two days perfecting something that does not work. You can be sure that the lack of success was not because that shade of orange was not exactly as you would have liked it.

You also need to be bold. You have no brand and thus no brand equity to erode. When working with large companies in an agency, you have to be careful with your messaging. You have to be politically correct, don’t go off brand, don’t throw shots at anyone blah blah blah….

This is your advantage as a start-up. Don’t be afraid to take a stand, be bold in your messaging and do something provocative. A company that I think nailed this quite well is TransferWise.

The worst case scenario is that there is an exclusively negative reaction. And in that case, it will be forgotten the day after. No one really cares about your startup at this stage. Plus you probably got some free backlinks anyways… like when SuperGurl decided to do a ‘rape us now’ campaign for black monday.

Victor on Twitter

The @SHOPSUPERGURL meeting where this was decided... "Screw it, we need free PR and backlinks" #growthhacking #seohttp://ind.pn/1OuI0Z1

You’re the expert

Become one if you’re not.

In the early stages, you will usually be hired as the expert and expected to make your own decisions. There most likely won’t be any managers telling you what to do. Depending on the founding team, you might be more or less a lone wolf when it comes to tactics. Embrace this and enjoy the freedom and responsibility it brings. Some final points of advice:

1. I would advise you to build a network of other growth marketers you can spar with. Join Slack groups (check Hamsterpad.com — I would recommend: Online Geniuses) and start joining in discussions. Ask if anyone is working in the same space as you and connect with them. I met a lot of interesting people this way and have formed great friendships and business connections.
2. If you are not an expert, become one. Read, read, read. A good starting point is Tractio by Justin. Find blogs and be sure to read about both strategy and tactics. Never stop reading. It’s the most important part of your job and you should set aside at least 30 min to 1 hour for reading every day.

For strategy, I would recommend Andy Johns and Brian Balfour as a good starting point:

1. Andy Johns (and rest of First Round team)
2. Brian Balfour
3. Chamath Palihapitiya

For tactics, I would advise you to read the following blogs:

1. Growthhackers.com
2. Inbound.org
3. YouMoz

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