21 • AI/Post-training • Engineer • Building https://nitter.gq/t.co/j66LuXVbKy, 8x-w6ykxw
mentally at SF
Joined August 2024
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rakesh retweeted
Dear Prime Minister of India,
Let’s not confuse business competition with an attack on national pride.
Elon Musk isn’t asking to run India. He’s asking to offer a service in India. There’s a difference.
Yes, Starlink is expensive. No, it isn’t going to replace affordable broadband for every Indian household. But that doesn’t mean it has nothing to offer. For remote villages, isolated communities, and regions where laying cables is economically unviable, satellite internet could be a genuine alternative.
And let’s be honest about one thing: profit and public benefit are not mutually exclusive. Musk wants to make money. So do Indian telecom companies. The real question is whether a company can provide value while operating under Indian law.
If Starlink fails to compete on price, customers can choose alternatives. If it offers better connectivity in underserved areas, people should have the freedom to benefit from it.
India is a sovereign nation. It has every right to regulate foreign companies, protect its interests, and enforce its laws. But sovereignty should give us the confidence to welcome competition on our own terms, not the insecurity to treat every foreign entrant as a threat.
We cannot keep talking about becoming a global technology superpower while being suspicious of every new player entering our market.
Regulate the competition. Don't fear it. Let Indians decide whether the service is worth paying for.
Because ultimately, this isn't about Elon Musk's ego or India's pride. It's about whether Indian consumers get more choices, better connectivity, and access to technology that could make a real difference.
Dear Prime Minister Ambani,
Please accept my humble apologies for not realizing that you are the real boss of India.
Naturally, you would prefer to maintain your monopolistic exploitation of the great people of India, but would you nonetheless consider allowing Starlink to compete?
There are many areas of India, as there are in all countries, with no Internet access, which denies children the opportunity for education and for small businesses the opportunity to sell their goods to a global market. Starlink would change their lives for the better.
Thank you 🙏
rakesh retweeted
5G services are available in 99.9% of all districts across India.
The current average cost of mobile data in India sits around $0.09 per GB.
Honest question: where is Starlink needed actually and how can it beat these prices?
rakesh retweeted
i really hate to say it, but…
gemini who? 🏎️💨
Meta has released Muse Spark 1.3, their fourth Muse Spark model release in five months. Muse Spark 1.3 (max), which is in limited preview for Meta’s partners, scores 62 on the Artificial Analysis Intelligence Index, behind only Claude Fable 5.1 and Claude Opus 5. The variant available now, Muse Spark 1.3 (xhigh), scores 61 and ties with GPT-5.6 Sol (max) and Grok 4.6 (high). Both variants’ gains come primarily from improvements in agentic work and scientific capabilities
Muse Spark 1.3 (xhigh) enters the Artificial Analysis Intelligence Index at 61, up 4 points from Muse Spark 1.2 (57, August) and 8 points from Muse Spark 1.1 (53, July). It enters tied with GPT-5.6 Sol (max), Grok 4.6 (high), and Claude Opus 5 (high), and behind Claude Fable 5.1 (max, 66), Claude Opus 5 (max, 63), and Claude Fable 5 (max, 62)
Muse Spark 1.3 (max), which is in a limited preview stage, lands at 62. This higher index score is enabled by gains vs. Muse Spark 1.3 (xhigh) in Tau3-Bench Banking (52% vs. 47%) and GDPval-AA v2 (1,754 Elo vs. 1,709). Muse Spark 1.3 (max) is second only to Claude’s Fable and Opus variants in total score
Congratulations to @AIatMeta, @finkd, and @alexandr_wang on the release!
Key Takeaways:
➤ Continued improvement on agentic knowledge work tasks. At the launch of Muse Spark 1.2, we noted its significant gains in agentic knowledge work performance vs. Muse Spark 1.1. The latest iteration continues this trend, with Muse Spark 1.3 (xhigh) demonstrating a notable 12-point gain vs. Muse Spark 1.2 in Tau3-Bench Banking (35% to 47%), a 5-point gain in Terminal-Bench 2.1 (80% to 85%), and a new GDPval-AA v2 Elo of 1709 against its predecessor’s 1615. Muse Spark 1.3 (max) improves further on Tau3-Bench Banking (52%) and GDPval-AA v2 (1,754 Elo). This Tau3-Bench Banking score is #1 among all models. Muse Spark 1.3 (max) achieves these higher agentic work scores by using more turns and total reasoning tokens, reasoning 62% more on GDPval-AA v2 and 28% more on Tau3-Bench Banking compared to Muse Spark 1.3 (xhigh)
➤ The lowest cost per task for any model at 59+ on the Artificial Analysis Intelligence Index. Muse Spark 1.3 (xhigh) costs $0.55 per Intelligence Index task at Meta's unchanged $1.25/$4.25 per 1M token pricing ($0.15 for cached input), with its peers GPT-5.6 Sol (max) and Grok 4.6 (high) costing $0.95 and $0.94 respectively, a 70%+ premium. This places Muse Spark 1.3 (xhigh) on the Pareto frontier for Intelligence vs. Cost per Task. Its cost per task is higher than Muse Spark 1.2 ($0.40 per task), driven by ~57% more input tokens per task on agentic evaluations, with output tokens up only ~8%. Pricing for Muse Spark 1.3 (max) is not yet publicly available
➤ Scientific Reasoning results rose across the board, led by CritPt. CritPt was the standout non-agentic score gain vs. Muse Spark 1.2, with a material +8 points for the xhigh variant (18% to 26%), and GPQA Diamond achieved +4 points (90% to 94%), while Humanity’s Last Exam and SciCode each gained a more modest 2-3 points (45% to 47% and 56% to 59%, respectively). Muse Spark 1.3 (max) achieved roughly similar scores to the xhigh variant, gaining 2 points in Humanity’s Last Exam, tying on GPQA Diamond, and losing a point on CritPt vs. Muse Spark 1.3 (xhigh)
➤ Minor regressions in only two evaluations. Both Muse Spark 1.3 (xhigh) and Muse Spark 1.3 (max) dropped 4 points in AA-LCR (83% to 79%) when compared to Muse Spark 1.2, and AA-Omniscience (Accuracy) fell 3 points for xhigh and 1 point for max. The drops in AA-Omniscience (Accuracy) are due to a higher abstention rate (not answering questions when unsure), which also lowered the hallucination rate for Muse Spark 1.3 (xhigh)
Other model details (xhigh variant):
➤ Context window: 1M tokens, unchanged from Muse Spark 1.2
➤ Pricing: unchanged from Muse Spark 1.2: $1.25/$4.25 per 1M input/output tokens, with cache hits discounted to $0.15 per 1M
➤ Input modalities: text, image, video
➤ Availability: Meta's first-party API and Muse Code
rakesh retweeted
We used HFlow to evaluate the latest open weights VLMs for processing egocentric data.
This was based on @buildpbc's Egocentric-10k evaluation, which used Gemini 2.5 Flash to measure hand visibility and active manipulation.
How much each model agreed with the reported results:
- Gemini 2.5 Flash: 91.65% (baseline)
- GLM 5.3 Flash: 91.00%
- Gemma 4 26B-A4B: 90.87%
- Qwen 3.8 27B: 90.79%
- Inkling Small: 85.21%
Gemma was the standout. Its results were on par with Gemini while being 19x cheaper.
Both Gemma and Qwen models are practical to self-host, enabling private processing without data egress.
This suggests modern open weights VLMs are becoming good enough for large-scale egocentric data processing. The main differentiators are increasingly cost, throughput, output reliability, and ease of self-hosting.
rakesh retweeted
It’s really sad to see that @kirat_tw is being targeted this way, I understand even if something he missed in management, there should be a way to fix that, rather than targeting someone’s hardwork, for me that is highly disappointing to ruin someone’s hardwork.
- Few questions I would like to ask to people questioning him.
“You always say he bring in another cohort ” do you guys teach in that cohort for continuous 3hr per lecture for 6-7 months. Why cant you admit his hardwork he puts in. I have seen those era where people dont know the tech stack and he made us all aware of things which looks too easy to learn these days( specially for tier-3 college students).
- one allegation is made that he js jealous of his people doing better than him, I have seen him giving platforms to people @kshvyaps is another one of them.
- due to the @100xDevs community I have came across so many cracked devs and that helped me in my growth. And I should always thank him for creating the community.
-He might have failed in so many things but he taught that there are endless possibilities one can achieve working remotely. Where did he guarantee you something? Share me one clip where is guarantees job or after his cohort you will master that skill.
-He uplifted himself from ground watch his story with his mother, business is not a thing where you can’t expect ups and downs ( for ex: watch the Paytm thing or many other , initially went good failed and came back stronger, thats how things are).
Take accountability for yourself and stop blaming people if you want to grow.
idk what’s actually going on rn or who’s right/wrong.
all i know is @kirat_tw genuinely helped me become a better developer. because of his cohort, i also made my first dollar from tech.
so yeah, i’m with Harkirat on this one.
rakesh retweeted
This is 1 million % true.
