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John Gaeta, Founder and CEO of Escape.ai – Interview Sequence

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John Gaeta, Founder and CEO of Eescape.ai, is a visionary innovator finest identified for his Academy Award-winning work on The Matrix trilogy. A pioneer in immersive media and future-facing applied sciences, Gaeta has spent his profession exploring the fusion of storytelling, real-time rendering, spatial computing, and synthetic intelligence to push the boundaries of how audiences expertise narrative worlds.

With escape.ai, Gaeta is now targeted on showcasing the following technology of AI-generated and AI-enhanced movie content material. The platform serves as a curated area for cutting-edge audiovisual experiences powered by generative AI, highlighting the way forward for storytelling by means of experimental codecs and clever media. By spotlighting this rising wave of inventive work, Escape.ai is redefining what streaming appears like within the period of synthetic intelligence.

What impressed the founding of Escape.ai, and the way does it tie into your long-standing mission to reinvent cinematic storytelling by means of know-how?

escape.ai was born from a really private mission: to empower creators to inform epic tales — with out asking for permission. For many years, Hollywood has been the gatekeeper of cinematic scale. However with AI, real-time engines, and immersive codecs, we now have the instruments to let any creator rival the scope of a studio. escape.ai is about constructing that bridge — a platform the place visionary storytellers can wield next-gen instruments to form worlds, personal their IP, and go head-to-head with the giants. It’s about democratizing leisure.

You’ve described Escape as a “Neo Cinema” platform. Are you able to outline what Neo Cinema means to you and the way it differs from conventional and even fashionable digital cinema?

Neo Cinema is a spirit and motion that’s pushing the following paradigm of storytelling and story-world making. It’s constructed upon the foundations of cinema whereas additionally disrupting and evolving it.

Parts of Neo Cinema:

  • Disruptive Content material Making Strategies & Applied sciences (Gen Ai, Recreation Engines, New tech)
  • Conventional and Ingenious Varieties and Codecs for Storytelling & World Constructing
  • Trendy, Agile and Tech Empowered Creator Class

From The Matrix to Magic Leap to ILMxLAB to Epic Video games to Inworld ai, you’ve all the time labored on the intersection of story and tech. How has that journey knowledgeable the DNA of Escape.ai?

My journey’s all the time been about increasing the methods tales and worlds may be skilled and breaking narrative constraints. With The Matrix, we glimpsed digital myth-making. At Magic Leap and ILMxLAB, we experimented with blurring actuality with beloved worlds like Star Wars. At Epic, we showcased the following plateau of cinematic-interactive platforms. And at Inworld we catalyzed the primary steps towards clever Characters. Escape.ai is the place all of it comes collectively — and the place creators, not companies, maintain the keys. This DNA is vital: we’re not simply innovating codecs; we’re redistributing energy. With AI and real-time instruments, creators can now compete with legacy studios — on their very own phrases. Escape.ai exists to make that imaginative and prescient actual.

What are probably the most thrilling or transformative methods you’re seeing Generative AI and sport engines utilized in storytelling at this time?

What excites me most is that the inventive asymmetry is disappearing. With generative AI and sport engines, a small workforce — or perhaps a solo creator — can now prototype complete worlds, animate characters, generate visible results, and scale concepts in days, not months. These aren’t shortcuts — they’re power multipliers. We’re seeing creators take dangers, inform private epics, and go direct-to-audience. AI doesn’t simply amplify the pure skills of human storytellers; it ranges the enjoying discipline by permitting new voices to be heard. It provides indie storytellers the means to launch franchises — and on escape, they really personal them.

Do you imagine AI filmmaking will ultimately merge with conventional Hollywood, or are we witnessing the start of a completely new trade?

We’re witnessing each. Hollywood will soak up a few of these instruments — it already is. However on the identical time, we’re seeing a brand new wave of storytellers who aren’t ready for entry. They’re constructing their very own ecosystems — decentralized, creator-owned, and tremendous tech empowered. It’s not only a technological shift; it’s an financial one. When creators use subsequent technology instruments to make blockbuster-quality content material and distribute it by means of platforms like escape.ai— whereas retaining their IP — we’re not simply evolving an trade. We’re making a parallel one.

How do you reply to skepticism across the inventive legitimacy of AI-assisted content material? Can these tales nonetheless be “human”?

The human coronary heart and thoughts continues to be the supply. Human authors are floor zero if one thing able to genuine human resonance is the target. AI instruments are simply extending the attain of human creativeness, in the identical means that particular results enabled the making of The Wizard of Oz or 2001: A House Odyssey. Early laptop graphics made movies like TRON attainable and as soon as it arrived, have been individuals frightened that human creativity would go extinct as a result of we have been turning to computer systems to change into our subsequent paint brush? No. The tales are nonetheless ours — our fears, our hopes, our myths — solely now we will categorical them extra vividly, extra flexibly, and extra independently. AI doesn’t change creativity; however can assist to take away the obstacles between imaginative and prescient and realization. And since creators can now construct and publish with no large finances or company backing, we’re really seeing extra human tales — from extra voices — than ever earlier than. Authenticity thrives in freedom.

In your view, what position will human authors and actors play in the way forward for AI-powered cinema?

They’ll be on the middle — however in new methods. Writers received’t simply script linear plots; they’ll design narrative ecosystems. Actors will mix bodily and digital performances, creating personas that persist throughout mediums. What adjustments is the canvas — not the soul. AI permits human creators to do extra, sooner, and with fewer constraints. It additionally provides them management over the avatars, characters, and universes they create — and the flexibility to monetize these property instantly. We’re getting into an period of inventive sovereignty.

You’ve got stated Escape.ai isn’t nearly know-how however about discovering “masters of a brand new craft.” What are the brand new expertise at this time’s filmmakers must thrive on this hybrid inventive world?

At this time’s new masters generally suppose like methods designers. With unprecedented entry to speedy iteration they can fail quick and study from errors main to higher understanding of story and construction — world-building, and viewers receptivity. This yr and past we are going to see an amazing convergence between this pioneer sector and the pre current sector of pure inventive danger takers, good writers, producers and performers which are usually pissed off by the “hollywood” media advanced they’ve contributed a lot to but are constrained by. Most significantly, the trendy creator is starting to grasp the worth of possession as they change into ever extra cautious of outdated paradigm exploitation. No less than I hope they’re. It’s not sufficient to make one thing lovely — you must personal your world, defend your IP, and construct sustainable paths on your work. Escape.ai exists to assist that complete inventive cycle — from spark to storyworld to platform.

You’ve described Escape.ai as a “Netflix for Neo Cinema.” What does that have seem like for viewers — and the way does it differ from a standard streaming platform?

Escape.ai seems on its face as a superbly offered streaming service however it’s not simply the place you watch — it’s a vacation spot you possibly can enter. Past the brand new world of innovative authentic content material there are social locations the place the creators hang around, meet one another and meet followers. Locations corresponding to our social feed or our majestic retro future immersive theater. Any customer to flee can select to observe movies historically or they will actually hit an escape button and discover themselves inside a social interactive theater the place they will watch and rejoice with associates. It’s a spot the place tales can evolve, the place creators can converse on to audiences, and the place followers can assist and affect what will get made subsequent. And since the creators personal their work, they will additionally develop it throughout video games (Neo Play is being developed now), sequence, merch— with out dropping management. That’s the ability of Neo Cinema.

You’ve launched options like digital theaters and creator journals — are you able to discuss how Escape is blurring the traces between streaming, social, and creator economies?

Escape.ai is designed to carry creators and audiences into the identical area — not simply as viewers, however as a group. Digital theaters enable real-time premieres with international participation. Creator journals provide transparency and perception into the inventive course of. It’s not simply leisure — it’s an ecosystem. And we’re tying this to financial fashions that reward creators for engagement, not simply views. IP possession turns into the muse for a real creator financial system — the place success is shared, and followers really feel linked to the worlds they assist elevate.

Escape.ai empowers creators to retain possession of their IP — a rarity in at this time’s leisure world. How essential is that to your philosophy?

It’s the core of our philosophy. With out possession, creators are labor. With possession, they’re architects of tradition. At Escape.ai, we’re constructing a world the place artists don’t must promote their rights to inform their tales. They construct as soon as, personal ceaselessly, and develop their IP throughout codecs. Emergent tech like GenAI makes it simpler to provide content material — however publishing that content material permits fan bases to emerge and that makes ip extra worthwhile, as a result of it could actually scale throughout video games, simulations, sequels, even merchandise. We would like creators to not solely make iconic worlds — however to personal the mythology. All that stated, the individuals behind escape are actually creators as nicely. We now have each intention in collaborating with most of the creators on escape in pursuit of our personal originals.

For a younger filmmaker or sport artist studying this — what’s your recommendation on getting began in Neo Cinema?

Begin constructing your universe — even when it’s small. Use the instruments — sport engines, AI mills, world editors — and study by doing. Don’t watch for permission. Don’t watch for a greenlight. You may create cinematic content material at this time. In case your concepts are compelling you may even problem something on streaming platforms. What issues most is your voice. That is the time for daring creators to step ahead. The gates are open. Please know that escape is for creators throughout the spectrum, from the newly minted to the extremely established. If you wish to sidestep the system, and inform the story you need not the one you’ve been advised you will need to, flip to Neo Cinema.

Thanks for the nice interview, I urge readers to go to escape.ai and watch a couple of shorts to expertise the way forward for video streaming and digital story telling.

Revolutionizing AI Safety and Cyber Resilience with Open-Supply Innovation and Danger Administration Options


Basis AI: Open-Supply Improvements for Safe AI

To deal with new and sophisticated cybersecurity challenges launched by the fast adoption of synthetic intelligence (AI), Cisco launches Basis AI, a staff of main specialists in AI and cybersecurity. This group is totally devoted to fixing main safety challenges of the AI period by creating superior instruments and applied sciences that sort out these core points.

This new strategy displays the urgent have to stability fast AI adoption with strong safety measures. Basis AI’s instruments is not going to solely empower organizations to defend towards rising threats however can even help coverage objectives to create moral and safe AI methods.

The Basis AI staff has simply launched the first-ever open-source reasoning mannequin designed particularly for safety functions. They’re additionally introducing benchmarks to check how properly cybersecurity fashions carry out in real-world situations, in addition to instruments that groups can leverage to customise and enhance their very own fashions. These efforts will foster collaboration between safety specialists, machine studying engineers, and AI builders, offering sensible options that companies can instantly leverage to enhance their cybersecurity methods.

The open-source instruments and benchmarks launched by Basis AI help the EU’s objectives to foster collaboration and transparency in expertise improvement. By encouraging the usage of safe and moral AI, Cisco’s initiatives contribute to the EU’s imaginative and prescient of a digital ecosystem that prioritizes security, resilience, and innovation, for companies and society at giant.

AI Provide Chain Danger Administration: Stopping Malicious or Dangerous AI Earlier than Hurt

Cisco is enhancing its AI Provide Chain Danger Administration capabilities to assist organizations sort out the rising challenges of managing AI safety dangers and safely undertake and innovate with AI. These instruments shield organizations by figuring out and stopping malicious or dangerous AI fashions earlier than they’ll trigger hurt. As an example, they’ll:

  • robotically detect and block AI fashions with dangerous or restrictive open-source software program licenses that pose mental property and compliance dangers;
  • implement insurance policies on AI fashions originating from geopolitically delicate areas;
  • detect and stop the usage of dangerous AI fashions within the group’s surroundings.

These developments are half of a bigger imaginative and prescient to combine safety at each stage of AI adoption, safeguarding organizations within the quickly evolving AI panorama.

Safe AI Deployment and Resilience

With the AI Act, the EU offered a framework to handle dangers related to AI and promote its reliable use, with an emphasis on making high-risk AI methods correct, strong and safe. Cisco’s strategy and applied sciences might help deployers and customers of those methods ensure that is the case.

This focus additionally comes because the EU positions itself within the world AI panorama, with important investments aimed toward creating an AI-ready continent. Instruments like these launched by Cisco’s  Basis AI improve the resilience of AI deployment throughout Europe, aligning with the EU’s ambition to guard crucial infrastructure, guarantee compliance, and reinforce cybersecurity.

As AI adoption accelerates, these efforts exemplify the necessity for a balanced strategy—one which embraces innovation whereas safeguarding towards rising dangers. By constructing sensible options, initiatives like Basis AI not solely strengthen safety but additionally advance the collective imaginative and prescient of a safe and moral AI future.

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react native – Bug: iOS autofill persists throughout screens, breaking InputBox


Situation

I’ve carried out a easy wrapper round a TextInput element, and I’m utilizing it in a number of screens.

Within the app move, the person:

  1. Indicators-up utilizing electronic mail/password
  2. Is redirected to a profile creation display

After I let iOS autofill a “new safe password” on the sign-up web page, after it being profitable, the TextInput on the subsequent display is yellowed-out as if iOS had autofilled one thing in, however the textual content field is empty. From there I can faucet on the TextInput which pulls up the keyboard, I can kind in letters, however nothing really occurs.
I’ve carried out logic to stop the person persevering with with out coming into some textual content in there, so the person is basically caught (which I’ve eliminated for this demo).

There a number of consecutive profile creation screens. The opposite TextInput fields are additionally affected, till the third display for some purpose.

bug in action

Disabling autofill, secureTextEntry, or setting textContentType to none on InputFields (which are not the password ones) doesn’t work.
I believed it could possibly be some buried state I unintentionally preserve, or a misused reference. Or one thing to do with routing? I am at a little bit of a loss, and will use some assist understanding how this will come about.

Code

TextInput wrapper element:

import React from "react";
import {
  StyleSheet,
  Textual content,
  View,
  TextInput,
  TextInputProps,
  Dimensions,
  TouchableOpacity,
} from "react-native";
import { useColors } from "@/parts/ThemeProvider";
import { Eye, EyeOff } from "lucide-react-native";

const { width } = Dimensions.get("window");

interface CustomInputProps extends TextInputProps {
  label: string;
  error?: string;
  isPassword?: boolean;
  disableAutofill?: boolean;
}

export const CustomInput: React.FC = ({
  label,
  error,
  isPassword = false,
  disableAutofill = false,
  ...props
}) => {
  const colours = useColors();
  const [secureTextEntry, setSecureTextEntry] = React.useState(isPassword);

  const toggleSecureEntry = () => {
    setSecureTextEntry(!secureTextEntry);
  };

  return (
    
      {label}
      
        
        {isPassword && (
          
            {secureTextEntry ? (
              
            ) : (
              
            )}
          
        )}
      
      {error && {error}}
    
  );
};

I don’t use anything special with the component:

const [name, setName] = useState("");


  

Any concepts on what I needs to be trying into to debug this?

Different Infos

  • Expo 52.0.36
  • React Native 0.76.7
  • React 18.3.1
  • iOS 18.4.1

IBM goals for autonomous safety operations



“IBM’s proactive menace looking augments conventional safety options to uncover anomalous exercise and IBM’s proactive menace hunters work with organizations to assist establish their crown jewel belongings and significant issues. This enter allows the menace looking crew to create totally tailor-made menace hunt studies and customised detections,” IDC acknowledged. “AI/ML capabilities filter alerts based mostly on exercise noticed throughout its total international footprint of safety operations facilities for the previous two years, decreasing false positives and accelerating detection, so groups can deal with high-priority threats, together with uncommon occasion detection.”

R&D for mainframe, quantum

IBM additionally introduced it’ll make investments $150 billion within the U.S. over the following 5 years. That features an funding of greater than $30 billion in analysis and improvement to advance and proceed IBM’s manufacturing of mainframe and quantum computer systems.

IBM not too long ago introduced the subsequent era of its venerable mainframe system, accessible in June. 

On the coronary heart of the brand new z17 mainframe is the 5.5 GHz IBM Telum II processor, which features a built-in AI accelerator that IBM says will let clients run greater than 450 billion inferencing operations in a day with one millisecond response time. The processor helps eight CPU cores per chip, 32 cores per system, and 36MB L2 cache reminiscence, and it will probably run 24 trillion operations per second – a 40% enhance in system throughput and fourfold discount in general latency in comparison with the prevailing Telum, IBM acknowledged.

On the quantum computing entrance, IBM has been creating techniques for plenty of years and claims to have the biggest fleet of quantum computer systems within the trade. Late final 12 months, IBM launched its most superior quantum laptop so far that includes the 156-qubit Heron quantum processor. That system doubled the earlier IBM system’s quantum computing capability and accomplished a activity in 2.2 hours that beforehand took 112 hours.

IBM’s quantum roadmap has the corporate delivering a completely error-corrected system in 2029. It expects to have a quantum laptop with over 2,000 error-corrected qubits — or logical qubits — after 2033. Its Quantum Community offers entry to IBM’s quantum techniques for almost 300 Fortune 500 corporations, educational establishments, nationwide laboratories, and startups and is accessed by over 600,000 lively customers, the corporate mentioned.

Glacier brings in $16M and proclaims new Recology King deployment

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Glacier brings in M and proclaims new Recology King deployment

Two Glacier programs at work in an MRF in Chicago. The robots can kind as much as 45 objects per minute. | Supply: Areeb Malik, co-founder of Glacier, on LinkedIn

Glacier, which makes use of synthetic intelligence and robotics to effectively kind recyclable supplies, right now introduced that it has raised $16 million in Collection A funding. The corporate additionally stated Recology’s King County Materials Restoration Facility, or MRF, in Seattle has deployed a fleet of its AI recycling robots.

San Francisco-based Glacier stated this funding caps a breakthrough interval throughout which it expanded its presence to markets together with San Francisco, Los Angeles, Chicago, Detroit, and Phoenix.

“The funding is just not solely an unimaginable testomony to this progress trajectory that we’re on, on our quest to allow round manufacturing; however we’re utilizing the funding in a few notable methods,” Rebecca Hu-Thrams, co-founder and CEO of Glacier, instructed The Robotic Report. “The primary is simply to make our {hardware}, together with our robotic and our imaginative and prescient programs, more and more extra scalable and sooner to deploy.”

Glacier has assembled robots to sort out the unpredictable nature of recycling streams. Its pc imaginative and prescient and AI expertise should determine and type over 30 various kinds of supplies, which might vary from frequent objects akin to PET plastic and aluminum cans to particular packaging sorts like toothpaste tubes, cat meals tins.

Glacier builds out knowledge flywheel

Hu-Thrams stated that Glacier has more and more been taking a look at its recycling robots and AI knowledge as two components of the identical flywheel. The info makes the robots higher and extra correct, whereas the robots collect extra knowledge with each choose they make.

“What we’re actually centered on now’s constructing out that flywheel and in addition understanding how we will harness that knowledge to unravel issues that will even be agnostic of what the robotic is instantly meant to deal with,” Thrams stated. “Our final imaginative and prescient is for Glacier to change into a software that may be an working system for these recycling amenities.”

The Ecosystem Integrity Fund (EIF) led the spherical. It additionally included participation from current traders together with New Enterprise Associates (NEA), AlleyCorp, Overture Local weather VC, Amazon Local weather Pledge Fund, and VSC Ventures.

New traders in Glacier included Elysium, Overlap Holdings, Cox Exponential, Alumni Ventures, One Small Planet, and Working Capital Fund.

Closing the round manufacturing loop

To know Glacier’s long-term objectives, you first want to know how the recycling worth chain works. It begins with placing recycling bins out on the curb. As soon as it’s there, the recyclables are picked up by a truck and brought to an MRF, Hu-Thrams stated.

“The job of that MRF is to principally to take that big pile of commingled recycling, a lot of which can also be trash, and type it into constituent commodities as successfully as doable,” she defined. “So if the sorting course of had been good, you’ll find yourself with these stunning bales of paper, cardboard, plastics, aluminum cans, and so forth that these MRFs might promote to finish market producers to show into new stuff. Now, the sortation course of, as you may in all probability think about, is extraordinarily cumbersome. It’s very costly, as a result of a lot of it’s nonetheless truly accomplished with handbook labor.”

MRFs expertise extraordinarily excessive ranges of turnover, and if most MRFs can’t discover the workforce, they’ll’t kind the waste into usable supplies. Hu-Thrams stated that Glacier is attempting to shut the loop in round manufacturing.

Ideally, supplies from recycling bins go to a facility, the place they’re damaged down into their particular person elements, repackaged, and delivered to a producing plant to be made into one thing else. Proper now, nevertheless, there’s a damaged hyperlink on this circle: the MRFs.

“Take into consideration what these MRFs are doing: They’re taking in feedstock, after which their job is to supply a sure yield at a sure high quality price, and do the entire high quality inspection you anticipate out of a typical manufacturing plant,” Hu-Thrams stated. “And but, they’ve so many fewer instruments than one thing like a plastic bottling plant.”

“They nonetheless have a heavy reliance on handbook labor,” she added. “They nonetheless have little by the use of knowledge at scale to assist them audit their processes and enhance effectivity. That’s actually the hole that Glacier is looking for to fill for them.”

Recycling poses sortation challenges

glacier robot.

Glacier stated its robotic prices half as a lot as standard choices and requires simply 3 ft. of conveyor area. | Supply: Glacier

MRFs are coping with an extremely heterogeneous stream of supplies which can be soiled and really troublesome to kind. This has offered many challenges for firms hoping to automate the method. First, earlier than Glacier, different recycling sortation programs used off-the-shelf robots, which had been usually too costly for the MRF, famous Hu-Thrams.

“Secondly, a number of these models had been simply bodily giant and really space-consuming in an atmosphere that could be very space-constrained,” she added. “Think about a robotic that takes up the area of three to 4 sorters on a kind line and does the job of 1.”

Lastly, MRFs, like manufacturing vegetation, reside or die primarily based on their upstream,” Hu-Thrams stated. “This implies they require very dependable programs that may keep working regardless of the extremely variable materials stream.

“They’re not simply processing bottles and cans and paper, but additionally seeing issues like Christmas lights and surfboards and microwaves and automobile motors and even issues like weapons and hand grenades,” she stated. “How do you design a system that’s versatile sufficient to work successfully with that form of materials stream? That is why we determined that purpose-built was the best way to go.”

Glacier makes use of off-the-shelf elements from dependable OEMs, Hu-Thrams stated. The firm sourced these components independently to place collectively a robotic that’s compact, has a excessive uptime, and a sooner return on funding (ROI). Actually, Hu-Thrams stated plenty of Glacier’s clients have gotten their ROI in lower than a 12 months. For recycling, a three-year turnaround can be thought-about quick, she stated.


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Glacier helps MRFs get essentially the most from the information it gathers

All through our dialog, Hu-Thrams emphasised Glacier’s dedication to placing its clients’ wants first. That is true in terms of prices, uptime, cost fashions, clients’ rights to service their robots, and, maybe most significantly, AI.

“We’ll go to our recycling facility clients and ask them, what are the commodities, or the forms of issues, that you just care essentially the most about?” Hu-Thrams stated. “We’ve truly used that strategy to flesh out the best way that we’re constructing our AI taxonomy.”

For instance, Glacier works to seek out methods for its clients to make use of their knowledge to enhance the general effectivity of the plant. “As we’ve grown out our database and as we’ve grown out the capabilities of AI, we’re truly seeing a lot of clients utilizing the information as a standalone product, like a typical manufacturing plant,” Hu-Thrams stated.

“We’ve truly helped quite a few clients determine and quantify as much as 1,000,000 {dollars} in incremental income they’re presently sending to the landfill yearly, after which we might help them fine-tune their plan and see real-time the place these adjustments made any impression to their total restoration price,” she continued.

Wanting ahead, Hu-Thrams stated that she hopes Glacier gained’t simply be a robotics or an AI knowledge firm, but additionally a companion to assist recycling amenities clear up top-line points. For instance, if a buyer was having issues with contamination in its paper stream, then Glacier might set up imaginative and prescient programs and robots in strategic places to assist enhance its purity price.

“We now, maybe for the primary time, can actually assist these amenities perceive in actual time, on the merchandise stage, what’s stepping into, what’s popping out of their bales, and what’s being ejected to the landfill,” stated Hu-Thrams. “We give them this restoration software to really make sure that they’re choosing in a selected manner.”