Adam Bittlingmayer

translation verification @modelfront Inschenör, Dolmetscher, πολυί̈στωρ, libertaire, օտար, rom po drom, 𒀲... Not available in your country.

[Adam Bittlingmayer @bittlingmayer]

@kartikb753 Let us know! MCP access to the core of the system of record is the bare minimum these days, IMHO. I use MCP in OpenLoc for everything from managing prompts to triggering projects to stats, i.e. more meta.

[Adam Bittlingmayer @bittlingmayer]

Every industry needs its open harness. We just shipped the open harness for the localization industry.

[OpenLoc @OpenLocTMS]

Full initial source code just dropped for the open, AI-native enterprise TMS!

Code and roadmap at https://t.co/imNh1IgTgy

This is a public beta, with lots of obvious features not built yet. We're already working on the next round: more file formats, CMS integrations, vendor management, portal... and more AI!

Want to shape the future? Teams in our Early Access Program get hands-on support and help decide what comes first on the way to General Availability. Apply at https://t.co/3N9iJLdkH1

[Adam Bittlingmayer @bittlingmayer]

Building is incredibly fun these days.

[OpenLoc @OpenLocTMS]

Full initial source code just dropped for the open, AI-native enterprise TMS!

Code and roadmap at https://t.co/imNh1IgTgy

This is a public beta, with lots of obvious features not built yet. We're already working on the next round: more file formats, CMS integrations, vendor management, portal... and more AI!

Want to shape the future? Teams in our Early Access Program get hands-on support and help decide what comes first on the way to General Availability. Apply at https://t.co/3N9iJLdkH1

[Adam Bittlingmayer @bittlingmayer]

Open harness → No AI tax!

[Slator @slatornews]

Adam Bittlingmayer, Co-founder and CEO of @modelfront, 🎙️ on why enterprises need an #AI-native Translation Management System (TMS).
#translation #TMS @OpenLocTMS @bittlingmayer
https://t.co/54Vns4xn8v

[Slator @slatornews]

Adam Bittlingmayer, Co-founder and CEO of @modelfront, 🎙️ on why enterprises need an #AI-native Translation Management System (TMS).
#translation #TMS @OpenLocTMS @bittlingmayer
https://t.co/54Vns4xn8v

[Adam Bittlingmayer @bittlingmayer]

@maxniederhofer I call it the “AI tax”.

[OpenLoc @OpenLocTMS]

Building enterprise software got a few X easier.

TMS buyers should be getting those same few X more in value.

https://t.co/cEQwXsHWqk

[Slator @slatornews]

Why @modelfront is offering a free, #AI-native #TMS with CEO Adam Bittlingmayer 🎙️ Check out https://t.co/xM0gMFbXdB 📺 Listen in 🎧 on Apple Podcasts 👉https://t.co/TZIfmvcoKX and Spotify 👉https://t.co/zNMjv0EvfR.
@OpenLocTMS

[Adam Bittlingmayer @bittlingmayer]

We launched the open harness for enterprise translation management.

[OpenLoc @OpenLocTMS]

OpenLoc is the open TMS built for AI.

Run raw MT at scale with no AI tax. Use any LLM, with context and RAG. Free integrations. System-wide MCP. Dashboards from chat. Run it yourself.

We’re giving it away for free. Source code on GitHub Oct 19 under the BSL 1.1 license.

https://t.co/3N9iJLdkH1

[Adam Bittlingmayer @bittlingmayer]

One more reason not to speak English inside the family, only arcane dialect.

[Tavus @tavus]

Introducing Griffin, the first model to pass the video Turing test.

48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video.

It’s the first Human Interaction Model (HIM).

[ModelFront @modelfront]

Translation AI is now featured at @Techweek_!

Join us on October 8th in downtown SF to hear from translation AI builders and localization teams from @Google, @Microsoft, @DeepLcom, @Meta, @modelfront and more!

#TechWeek, the world's largest decentralized tech gathering, brings together 100K+ attendees.

The #SFTechWeek translation AI event is organized by ModelFront and hosted by @Adobe.

Get on the guest list at https://t.co/P9ijRxUBTX

[George the Radical Centrist @gbittlingmayer]

The world based on the number of 0-4 year olds.https://t.co/U8XAehj60k

[Adam Bittlingmayer @bittlingmayer]

@Valen10Francois Intelligibility is basically always asymmetric, because it’s just so rare that the soft power balance is perfectly symmetric.

If it’s mutual, it just means that they both speak the same language.

[Adam Bittlingmayer @bittlingmayer]

@ArmenAgha Same thing happened in translation.

[Max Spero @max_spero_]

In my view we have a few different tiers of verifiability
1) programatically verifiable (near-free)
- games, coding, math, cybersecurity, chip design
2) real-world verifiable (cost-or time bounded)
- sciences: biology, chemistry, physics
-physical world: material science, energy, aerospace, robotics, agriculture, pharma
-forecasting: trading, weather
3) verifiable with human preference
- writing, design, comedy, charisma, persuasion

I expect most low-hanging fruit in (1) to be solved very quickly. Not sure how much longer before more solved math conjectures are simply uninteresting. I’m least certain about chip design being in this category, perhaps we hit a ceiling and require physics or materials breakthroughs to continue progress.

My guess is we will quickly run into the limits of how well we can simulate each domain in (2). The time-bounded nature of real world verification may be the reason we don’t hit fast takeoff. Sim2real remains an elusive problem to solve when real-world data is limited. Part of the reason I don’t expect to live multiple hundreds of years is simply that I expect pharmaceutical progress to be time-bounded by the physical world.

I expect the items in (3) to never really get solved to a superhuman degree, as success relies on an ever-shifting plane of cultural preference. People adapted to “good” AI writing and became annoyed at new stylistic tics that, in a vacuum, are not necessarily bad.

[andrew chen @andrewchen]

Unlimited mathematical proofs but limited skilled mathematicians who can verify them

Unlimited code but limited skilled programmers to review them

Unlimited videos but limited attention to watch them

Unlimited lawsuits but limited courts/judges/lawyers to adjudicate them

When the creation of something goes to zero, the cost moves elsewhere…

[Tibo @thsottiaux]

@_chenglou I was part of that team. Basically ChatGPT one year before it came out. Called LMChat and then another codename.

Google was too nervous to release it and DeepMind was blocked from shipping products that could disrupt Google.

I think about this a lot.

[Adam Bittlingmayer @bittlingmayer]

@pfau This is essentially what happened in translation, the original generative task. The logical next step is AI to do verification or flag for human intervention.