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FSD V14 - What Features Are Coming

KuMX

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https://www.notateslaapp.com/news/2526/whats-coming-next-in-tesla-fsd-v14

So, what’s next with FSD V14? Tesla gave us a sneak peek at what’s next for FSD.

FSD V14
The standout feature of FSD V14 will be auto-regressive transformers. While that’s a complex term for those unfamiliar with AI or machine learning, we’ll break it down.

Auto-Regressive
An auto-regressive transformer processes sequential data in time, using that information to predict future elements based on previous ones. Imagine completing a sentence: You use the words already written to guess what comes next. This process isn't just about filling in the blank; it's about understanding the flow of the sentence and anticipating the speaker's intent.

FSD could analyze a sequence of camera images to identify pedestrians and predict their likely path based on their current movement and surrounding context. The system's auto-regressive nature allows it to learn from past sequences and improve its predictions over time, adapting to different driving scenarios.

Today, FSD reacts to what it sees, but soon it’ll be able to anticipate what will help, much like humans.

Transformers
The second part of that term is transformer, which is a component used to understand the relationships of elements inside a time sequence. It identifies which parts of the input are most crucial for making accurate predictions, allowing the system to prioritize information much like a human would. Think of it as weighing different pieces of evidence to arrive at a conclusion. For example, a transformer might recognize that a blinking turn signal is more important than the color of the car when predicting a lane change.

Putting It Together
Putting all that together, Tesla’s use of auto-regressive transformers means they’ll be working on how FSD can predict the plans and paths of the world around it. This will improve FSD’s already powerful perception and allow it to predict how other vehicles and vulnerable road users (VRUs) will behave.

What it all comes down to is that FSD will be able to make better decisions and plan its paths by making more informed, human-like decisions. That will be a big step towards improving V13 - which already has some very effective decision-making.

Larger Model and Context Size
Ashok Elluswamy (Tesla’s VP of AI) stated that FSD V14 will see larger model and context sizes in FSD V14, which coincidentally are listed in the upcoming improvements section of FSD V13.2.6. If we compare what Ashok said to what’s listed in the upcoming features section, the model and context sizes should grow by 3x.

Interestingly, Ashok says that AI4’s memory limits context size. Context is essentially the history of what the vehicle remembers, which is used for future decisions. Since this information is stored in memory, it’ll always be limited by memory, but it’s worth noting that Ashok mentioned that Tesla is restricted by the memory in the AI4 computer.

Leverage Audio Input
Tesla is already gathering audio data in existing FSD versions so that it can start training models with audio as well, truly making FSD more human-like. According to Ashok, FSD V14 will be the first version to take advantage of audio input for FSD driving. This will primarily be used for detecting emergency vehicles, but we can see this expanding to other sounds that help humans adjust their driving, such as car crashes, loud noises, honking, etc. At the very least, FSD could be more cautious when hearing a noise that matches an accident or vehicle honking.

FSD V14 Release Date
We haven’t heard from Elon Musk or Ashok Elluswamy about when FSD V14 will arrive. Ashok previously stated that FSD V13.4 would see audio inputs being used, but at Tesla’s earnings call, Tesla said that audio input would become relevant in V14, making it seem like Tesla may scrap V13.4 for V14.

Since Tesla is planning to launch their Robotaxi network in Texas this June, which is just four months away, FSD V14 may be the version used for its autonomous taxi fleet.
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The CT doesn't even have half the features of V13. FSD from park, reverse, park at destination, 3x model scaling, Integrated unpark, reverse, and park, etc.

AI5 will be out this year. I assume some of the holdbacks in memory will be seen there.
 

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I just want to be able to use the app to pull the car forward and back in a parking spot. Would be nice if FSD could auto honk as well. In a near accident situation I would love it to honk the fire truck horn asap.
 

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Dumb summon should be a minimum level of functionally. Good luck getting Elon’s attention anymore to address these kinds of issues like we could in the past.
 

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https://www.notateslaapp.com/news/2526/whats-coming-next-in-tesla-fsd-v14

So, what’s next with FSD V14? Tesla gave us a sneak peek at what’s next for FSD.

FSD V14
The standout feature of FSD V14 will be auto-regressive transformers. While that’s a complex term for those unfamiliar with AI or machine learning, we’ll break it down.

Auto-Regressive
An auto-regressive transformer processes sequential data in time, using that information to predict future elements based on previous ones. Imagine completing a sentence: You use the words already written to guess what comes next. This process isn't just about filling in the blank; it's about understanding the flow of the sentence and anticipating the speaker's intent.

FSD could analyze a sequence of camera images to identify pedestrians and predict their likely path based on their current movement and surrounding context. The system's auto-regressive nature allows it to learn from past sequences and improve its predictions over time, adapting to different driving scenarios.

Today, FSD reacts to what it sees, but soon it’ll be able to anticipate what will help, much like humans.

Transformers
The second part of that term is transformer, which is a component used to understand the relationships of elements inside a time sequence. It identifies which parts of the input are most crucial for making accurate predictions, allowing the system to prioritize information much like a human would. Think of it as weighing different pieces of evidence to arrive at a conclusion. For example, a transformer might recognize that a blinking turn signal is more important than the color of the car when predicting a lane change.

Putting It Together
Putting all that together, Tesla’s use of auto-regressive transformers means they’ll be working on how FSD can predict the plans and paths of the world around it. This will improve FSD’s already powerful perception and allow it to predict how other vehicles and vulnerable road users (VRUs) will behave.

What it all comes down to is that FSD will be able to make better decisions and plan its paths by making more informed, human-like decisions. That will be a big step towards improving V13 - which already has some very effective decision-making.

Larger Model and Context Size
Ashok Elluswamy (Tesla’s VP of AI) stated that FSD V14 will see larger model and context sizes in FSD V14, which coincidentally are listed in the upcoming improvements section of FSD V13.2.6. If we compare what Ashok said to what’s listed in the upcoming features section, the model and context sizes should grow by 3x.

Interestingly, Ashok says that AI4’s memory limits context size. Context is essentially the history of what the vehicle remembers, which is used for future decisions. Since this information is stored in memory, it’ll always be limited by memory, but it’s worth noting that Ashok mentioned that Tesla is restricted by the memory in the AI4 computer.

Leverage Audio Input
Tesla is already gathering audio data in existing FSD versions so that it can start training models with audio as well, truly making FSD more human-like. According to Ashok, FSD V14 will be the first version to take advantage of audio input for FSD driving. This will primarily be used for detecting emergency vehicles, but we can see this expanding to other sounds that help humans adjust their driving, such as car crashes, loud noises, honking, etc. At the very least, FSD could be more cautious when hearing a noise that matches an accident or vehicle honking.

FSD V14 Release Date
We haven’t heard from Elon Musk or Ashok Elluswamy about when FSD V14 will arrive. Ashok previously stated that FSD V13.4 would see audio inputs being used, but at Tesla’s earnings call, Tesla said that audio input would become relevant in V14, making it seem like Tesla may scrap V13.4 for V14.

Since Tesla is planning to launch their Robotaxi network in Texas this June, which is just four months away, FSD V14 may be the version used for its autonomous taxi fleet.
Maybe we should be happy to see FSD trained on the Cybertruck rather than a Model X, and to actually get the V13 features that we never got.
 


Sjohnson20

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Two things I want most are:

Ability to drive in sunlight glare. Right now it's terrible. I have to take over between 4pm and 5pm when the sun sets. They will need to figure that out somehow if they want to have robotaxis.

I also wish it would stop making dumb lane change decisions. Today it decided to switch to the left lane for no reason with .3 miles left until a right turn. I thought we were done with that but it still has some issues with it.
 

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https://www.notateslaapp.com/news/2526/whats-coming-next-in-tesla-fsd-v14

So, what’s next with FSD V14? Tesla gave us a sneak peek at what’s next for FSD.

FSD V14
The standout feature of FSD V14 will be auto-regressive transformers. While that’s a complex term for those unfamiliar with AI or machine learning, we’ll break it down.

Auto-Regressive
An auto-regressive transformer processes sequential data in time, using that information to predict future elements based on previous ones. Imagine completing a sentence: You use the words already written to guess what comes next. This process isn't just about filling in the blank; it's about understanding the flow of the sentence and anticipating the speaker's intent.

FSD could analyze a sequence of camera images to identify pedestrians and predict their likely path based on their current movement and surrounding context. The system's auto-regressive nature allows it to learn from past sequences and improve its predictions over time, adapting to different driving scenarios.

Today, FSD reacts to what it sees, but soon it’ll be able to anticipate what will help, much like humans.

Transformers
The second part of that term is transformer, which is a component used to understand the relationships of elements inside a time sequence. It identifies which parts of the input are most crucial for making accurate predictions, allowing the system to prioritize information much like a human would. Think of it as weighing different pieces of evidence to arrive at a conclusion. For example, a transformer might recognize that a blinking turn signal is more important than the color of the car when predicting a lane change.

Putting It Together
Putting all that together, Tesla’s use of auto-regressive transformers means they’ll be working on how FSD can predict the plans and paths of the world around it. This will improve FSD’s already powerful perception and allow it to predict how other vehicles and vulnerable road users (VRUs) will behave.

What it all comes down to is that FSD will be able to make better decisions and plan its paths by making more informed, human-like decisions. That will be a big step towards improving V13 - which already has some very effective decision-making.

Larger Model and Context Size
Ashok Elluswamy (Tesla’s VP of AI) stated that FSD V14 will see larger model and context sizes in FSD V14, which coincidentally are listed in the upcoming improvements section of FSD V13.2.6. If we compare what Ashok said to what’s listed in the upcoming features section, the model and context sizes should grow by 3x.

Interestingly, Ashok says that AI4’s memory limits context size. Context is essentially the history of what the vehicle remembers, which is used for future decisions. Since this information is stored in memory, it’ll always be limited by memory, but it’s worth noting that Ashok mentioned that Tesla is restricted by the memory in the AI4 computer.

Leverage Audio Input
Tesla is already gathering audio data in existing FSD versions so that it can start training models with audio as well, truly making FSD more human-like. According to Ashok, FSD V14 will be the first version to take advantage of audio input for FSD driving. This will primarily be used for detecting emergency vehicles, but we can see this expanding to other sounds that help humans adjust their driving, such as car crashes, loud noises, honking, etc. At the very least, FSD could be more cautious when hearing a noise that matches an accident or vehicle honking.

FSD V14 Release Date
We haven’t heard from Elon Musk or Ashok Elluswamy about when FSD V14 will arrive. Ashok previously stated that FSD V13.4 would see audio inputs being used, but at Tesla’s earnings call, Tesla said that audio input would become relevant in V14, making it seem like Tesla may scrap V13.4 for V14.

Since Tesla is planning to launch their Robotaxi network in Texas this June, which is just four months away, FSD V14 may be the version used for its autonomous taxi fleet.
Thank you for the really helpful breakdown and explanation. It’s helpful when someone who understands the jargon can explain it in Laymans terms.
 

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https://www.notateslaapp.com/news/2526/whats-coming-next-in-tesla-fsd-v14

So, what’s next with FSD V14? Tesla gave us a sneak peek at what’s next for FSD.

FSD V14
The standout feature of FSD V14 will be auto-regressive transformers. While that’s a complex term for those unfamiliar with AI or machine learning, we’ll break it down.

Auto-Regressive
An auto-regressive transformer processes sequential data in time, using that information to predict future elements based on previous ones. Imagine completing a sentence: You use the words already written to guess what comes next. This process isn't just about filling in the blank; it's about understanding the flow of the sentence and anticipating the speaker's intent.

FSD could analyze a sequence of camera images to identify pedestrians and predict their likely path based on their current movement and surrounding context. The system's auto-regressive nature allows it to learn from past sequences and improve its predictions over time, adapting to different driving scenarios.

Today, FSD reacts to what it sees, but soon it’ll be able to anticipate what will help, much like humans.

Transformers
The second part of that term is transformer, which is a component used to understand the relationships of elements inside a time sequence. It identifies which parts of the input are most crucial for making accurate predictions, allowing the system to prioritize information much like a human would. Think of it as weighing different pieces of evidence to arrive at a conclusion. For example, a transformer might recognize that a blinking turn signal is more important than the color of the car when predicting a lane change.

Putting It Together
Putting all that together, Tesla’s use of auto-regressive transformers means they’ll be working on how FSD can predict the plans and paths of the world around it. This will improve FSD’s already powerful perception and allow it to predict how other vehicles and vulnerable road users (VRUs) will behave.

What it all comes down to is that FSD will be able to make better decisions and plan its paths by making more informed, human-like decisions. That will be a big step towards improving V13 - which already has some very effective decision-making.

Larger Model and Context Size
Ashok Elluswamy (Tesla’s VP of AI) stated that FSD V14 will see larger model and context sizes in FSD V14, which coincidentally are listed in the upcoming improvements section of FSD V13.2.6. If we compare what Ashok said to what’s listed in the upcoming features section, the model and context sizes should grow by 3x.

Interestingly, Ashok says that AI4’s memory limits context size. Context is essentially the history of what the vehicle remembers, which is used for future decisions. Since this information is stored in memory, it’ll always be limited by memory, but it’s worth noting that Ashok mentioned that Tesla is restricted by the memory in the AI4 computer.

Leverage Audio Input
Tesla is already gathering audio data in existing FSD versions so that it can start training models with audio as well, truly making FSD more human-like. According to Ashok, FSD V14 will be the first version to take advantage of audio input for FSD driving. This will primarily be used for detecting emergency vehicles, but we can see this expanding to other sounds that help humans adjust their driving, such as car crashes, loud noises, honking, etc. At the very least, FSD could be more cautious when hearing a noise that matches an accident or vehicle honking.

FSD V14 Release Date
We haven’t heard from Elon Musk or Ashok Elluswamy about when FSD V14 will arrive. Ashok previously stated that FSD V13.4 would see audio inputs being used, but at Tesla’s earnings call, Tesla said that audio input would become relevant in V14, making it seem like Tesla may scrap V13.4 for V14.

Since Tesla is planning to launch their Robotaxi network in Texas this June, which is just four months away, FSD V14 may be the version used for its autonomous taxi fleet.
Ku,

One question I have, will FSD ever be capable of learning individual driver or individual truck preferences?

For example, I may prefer to drive a little faster than the prevailing traffic and prioritize the left lane while another driver prefers to stay with the traffic flow and ride in the right lane. Will FSD be capable of learning the preferred driving behavior at the individual truck level or will all FSD vehicles, in general, react exactly the same given similar situations (and yes, I know we have a few "selections" that allow some degree of customization).
 

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Ku,

One question I have, will FSD ever be capable of learning individual driver or individual truck preferences?

For example, I may prefer to drive a little faster than the prevailing traffic and prioritize the left lane while another driver prefers to stay with the traffic flow and ride in the right lane. Will FSD be capable of learning the preferred driving behavior at the individual truck level or will all FSD vehicles, in general, react exactly the same given similar situations (and yes, I know we have a few "selections" that allow some degree of customization).
No.

That's not how FSD or HW3/AI4/AI5 is designed. There's not enough memory. There will be less user input as it advances. This is how FSD was designed per Karpathy, Ashok, and Elon. As Elon said, "All user input is error".

We are losing options as FSD advances and that will continue. There will never be local learning on the car unless Tesla completely changes gears with their model and we know that's not happening with AI4 or AI5.

There have been talks in the future about being able to tell the car to take a left ahead and other inputs (like in a taxi), but it's not going to learn based on your preferences.
 

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I wanted to point out that memory is the limiting factor in most AI systems. You could triple or even add a couple orders of magnitude more memory but use it all with just a parameter change. You should always use all of your memory. It’s a bit of a game of diminishing returns though. You can add more memory at a much higher cost but should you. That’s where training and tuning comes in. Use all of the memory that’s available as efficiently as possible. Less about compressing bit and more about only storing what you need.

All of that to say, just because they are out of memory doesn’t mean AI4 can’t meet the goal. It also doesn’t mean that just adding memory in AI5 solves the problem. Most of the effort goes into the software. Better hardware makes the software easier after you meet the minimum threshold (which they are saying HW3 can’t make).
 


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I wanted to point out that memory is the limiting factor in most AI systems. You could triple or even add a couple orders of magnitude more memory but use it all with just a parameter change. You should always use all of your memory. It’s a bit of a game of diminishing returns though. You can add more memory at a much higher cost but should you. That’s where training and tuning comes in. Use all of the memory that’s available as efficiently as possible. Less about compressing bit and more about only storing what you need.

All of that to say, just because they are out of memory doesn’t mean AI4 can’t meet the goal. It also doesn’t mean that just adding memory in AI5 solves the problem. Most of the effort goes into the software. Better hardware makes the software easier after you meet the minimum threshold (which they are saying HW3 can’t make).
Does anyone know when we are getting smart summons
 

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Two things I want most are:

Ability to drive in sunlight glare. Right now it's terrible. I have to take over between 4pm and 5pm when the sun sets. They will need to figure that out somehow if they want to have robotaxis.

I also wish it would stop making dumb lane change decisions. Today it decided to switch to the left lane for no reason with .3 miles left until a right turn. I thought we were done with that but it still has some issues with it.
Have you had the inner surface of the windshield cleaned in front on the cameras?
Tesla has a service procedure for this which is needed due to interior outgassing.

If you are in Hurry mode, it favors the left lane.
 

Sjohnson20

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Have you had the inner surface of the windshield cleaned in front on the cameras?
Tesla has a service procedure for this which is needed due to interior outgassing.

If you are in Hurry mode, it favors the left lane.
Yes I had the truck in service twice and the windshield cleaning was done. The sunlight glare issue happens on all my Teslas.

I was on chill when it changed lanes with .03 miles.
 

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Yes I had the truck in service twice and the windshield cleaning was done. The sunlight glare issue happens on all my Teslas.

I was on chill when it changed lanes with .03 miles.
Gotcha, post cleaning I've had zero sunlight induced disengagements.
 

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Does anyone know when we are getting smart summons
Whenever Cybertruck drivers put in enough road miles on FSD so we can have a native model rather than a parameter swapped emulated one. So technically its up to us lol
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