HN user
I think World models is way to go for Super Intelligence. One of teh patent i saw already going in this direction for Autonomous mobility is https://patents.google.com/patent/EP4379577A1 where synthetic data generation (visualization) is missing step in terms of our human intelligence.
Recently saw this useful video on colors https://aeon.co/videos/after-centuries-of-trying-weve-yet-to...
May I know what is the name of app that is built using LLM? 10k MRR is highly successful app.
Now the fourth element is the seminal paper " Attention is all you need" which has taken AI into next level with openAI LLMs and the likes. Another story that rightly fits in here. https://www.ft.com/content/37bb01af-ee46-4483-982f-ef3921436...
this is a reality in organisation: " it’s paradoxically often better for you if there is some kind of problem that forces a delay, for the same reason that the heroic on-call engineer who hotfixes an incident gets more credit than the careful engineer who prevents one." Its ironic in many areas. A leader (Project or Political) who ran projects and shipped smoothly is less valued than a leader who created a mess and got them fixed ...who is more celebrated. :(
we used to use Fixed point multiplications (Q Format) in DSP algorithms on different DSP architectures. https://en.wikipedia.org/wiki/Q_(number_format). They used to be so fast and near accurate to floating point multiplications. Probably we need to use those DSPs blocks as part of Tensors/GPUs to realise both fast multiplications & parallelisms.
I found this one to be useful. OpenGL GUI based demos: http://www.songho.ca/opengl/
Can any expert in this domain validate the claimed performance over H100? Any pointers on how optical processors work and how mature they are over traditional processors.
When I began my career as a DSP optimization engineer, I worked on ZSP processors. I had a particular passion for branch predictions. By analyzing data, we would code and recode branch instructions to minimize mispredictions. I loved that super- scalar architecture of ZSP and its Branch prediction feature was amazing, apart from its multi Instruciton execution in a cycle.
India recently concluded its general elections. However, some opposition parties in southern states, who suffered significant losses, are alleging tampering, hacking, and even replacement of "lost EVMs" (Electronic Voting Machines). Is this possible? EVMs are generally not connected to WiFi or Bluetooth, but are there other ways the system could be manipulated as claimed by the losing parties? what do you think?
Chandrayaan-3, Successfully Soft landed. Amazing feat by ISRO. Kudos to all engineers behind this.
I have similar situation at home. I am from guess culture and always think about what the guests might need and offer them ahead. But my wife expects them to ask and doesn't bother much or ignores them. I see people from guess culture tend to be more empathetic as they think from others POV but the downside is they have anxiety of what others might judge and be more stressed. Ask culture people tend to be more situationally unaware and don't bother much and are relaxed.
Recent article on this topic. Off late am curious to know more on consciousness. https://aeon.co/essays/how-blindsight-answers-the-hard-probl...
This infographic gives better perspective
https://www.webfx.com/blog/internet/the-6-companies-that-own...
Its behind pay wall. Any other way to read this article?
But it turns out that Self driving cars must save people inside at any cost. If not,the whole purpose of selfdriving cars to reduce accidents (coz of human error) gets defeated. Because people prefer driving themselves than to buy self driving cars.
https://www.technologyreview.com/2015/10/22/165469/why-self-...
Best start would be to start with a word with maximum VOWELS.(PIOUS,SAUTE etc). Next guess can be based on previous yellows/greens.
If any one is interested to knwo how complex the chio making process is and why it is not so easy to set up a plant. https://youtu.be/CkNn98WE5_k
Reminds me of Dunning Kruger Effect: https://en.wikipedia.org/wiki/Dunning%E2%80%93Kruger_effect
How is it even an inventive step to be patentable?
The challenge I faced earlier was to get things executed ( expected outcome) from different teams. When I found my first follower , the one who really buys my vision and takes it down, things started to roll faster. This might give you an idea of first followers.
there are 10 types of people in this world, those who understand binary and those who dont.
In this article, there is a mention of "constant battle going on inside our brains between different sets of neurons, fighting over who gets control of certain parts of the brain." Because of which visual cortex always gets activated (even in sleep)so that it's neurons are not repurposed for other activities. Hence we dream. http://m.nautil.us/issue/91/the-amazing-brain/your-brain-mak...
SoftBank isa true banking company .. invested (Bought) in ARM and selling it now for meagre profit. A company that says it has 300 year vision
My son and his online class teacher uses lichess extensively. He is learning a lot with it.
This video summarises trolley problem well for driverless cars. https://youtu.be/ixIoDYVfKA0
Watch the exact scene how an owl catches its prey while they are totally ignorant. Watch for pair of lights(owlEyes) to see the onset of owl. https://youtu.be/2Ol4rbYPYQc
Even in broad day light and hith High Res videos and with ML algos, we cannot extract all information accurately that are needed. For example, at what velocity the other vehicle is moving and also at what distance we have an obstacle etc. is very difficult to extract from camera alone and impossible when it is night or extreme weather conditions. Hence we need Radar & Lidars also for ADAS & Self driving applications.
Radar: It can accurately measure Distance and Velocity information of objects around ego vehicle and also can track objects. It works well in all weather conditions (Day/night/rain/fog etc). Lidar: Good distance measurement, Rich in data (3D Point cloud) for ML, OK in doing classification (pedestrain, bicyclist etc) even in nights. But expensive sensor.
Now a days DL models are becoming commodities very fast. By the time you train NN to solve a particular problem, a new efficient model is out somewhere and is available public. So you need to go through the process entirely or else you risk losing business. Unless your NN is so unique like you are handcrafting your own in which case you take lot of time to arrive at a best model and you need more PhDs.
Can’t agree more. Currently I am in same situation. I lead a small core technical team that delivers cutting edge tech. My peers lead very big teams that do maintenance work. But my BU head measures success by how many people his reportees handle, new initiatives taken (process wise or fun wise etc ) that bring high visibility and mileage to him. He doesn’t bother about guiding and managing a technically motivated team that brings lot of innovations. He uses same yardstick for all.
Edit: grammar correction